CN102087362B

CN102087362B - Signal tracking methods and devices

Info

Publication number: CN102087362B
Application number: CN200910241403.4A
Authority: CN
Inventors: 邓中亮; 邹德君; 杨磊; 刘华东; 黄建明; 韩可; 徐连明
Original assignee: Beijing University of Posts and Telecommunications
Current assignee: Beijing University of Posts and Telecommunications
Priority date: 2009-12-08
Filing date: 2009-12-08
Publication date: 2014-04-16
Anticipated expiration: 2029-12-08
Also published as: CN102087362A

Abstract

The invention discloses a method and device for Kalman filter, digital phase-locked loop filter and signal tracking, belonging to the field of wireless communication. The signal tracking method includes: processing the received signal to obtain the received signal, and extracting the current observation value from the received signal, the received signal includes a received carrier and a received code; judging whether the speed, acceleration or jerk of the receiver is greater than If it is a preset threshold, the carrier is in a high dynamic environment, and the Kalman filter is used for signal tracking; if not, the carrier is in a non-high dynamic environment, and a digital phase-locked loop is used for signal tracking. The invention also discloses a signal tracking device, a Kalman filter method and device, and a digital phase-locked loop filter method and device. The method provided by the invention enables the receiver to switch the carrier tracking method adaptively, reduces the error of the loop, improves the refresh rate of the positioning result, and achieves the purpose of continuously tracking the signal without losing lock in a complex dynamic environment.

Description

Method and device for signal tracking

技术领域 technical field

本发明涉及无线通信领域，特别涉及一种卡尔曼滤波、数字锁相环滤波和信号跟踪的方法和装置。 The invention relates to the field of wireless communication, in particular to a method and device for Kalman filtering, digital phase-locked loop filtering and signal tracking. the

背景技术Background technique

卫星导航接收机基带信号处理模块中关键的部分是载波跟踪和码跟踪方法，接收到GPS卫星信号后，可以得到输入信号中载波多普勒频移值和码相位的估计值，这时接收机可转入跟踪状态，跟踪环路的作用是跟踪码相位变化和载波多普勒变化，从而实现接收机本地复现信号同输入信号的准确同步，提取准确的观测量和导航电文信息，进行接收机导航解算。 The key part of the satellite navigation receiver baseband signal processing module is the carrier tracking and code tracking method. After receiving the GPS satellite signal, the carrier Doppler frequency shift value and the estimated value of the code phase in the input signal can be obtained. At this time, the receiver It can be transferred to the tracking state. The function of the tracking loop is to track the change of code phase and carrier Doppler, so as to realize the accurate synchronization of the local reproduced signal of the receiver with the input signal, extract accurate observation data and navigation message information, and receive Machine navigation solution. the

现有技术中的载波跟踪和码跟踪方法主要有两种： There are mainly two types of carrier tracking and code tracking methods in the prior art:

第一种方法是将接收信号处理后经过卡尔曼滤波，得到新的观测值后，根据前一个估计值和最后一个观测数据来估计信号的当前值，特别适宜实时数据处理。 The first method is to process the received signal and pass it through Kalman filter. After obtaining the new observation value, estimate the current value of the signal according to the previous estimated value and the last observed data, which is especially suitable for real-time data processing. the

第二种方法是接收信号处理后经过数字锁相环，通过复现精确的载波频率和相位完成精确载波剥离。具体方法为：输入信号和本地载频进行混频，得到同相信号I和正交信号Q，通过低通滤波器和鉴相器之后得到载波信号和本地载波信号的相位差，该相位差信号对本地载波信号NCO(numerical controlled oscillator，数字控制振荡器)进行控制，产生新的载波。 The second method is to pass through a digital phase-locked loop after receiving signal processing, and complete accurate carrier stripping by reproducing accurate carrier frequency and phase. The specific method is: the input signal is mixed with the local carrier frequency to obtain the in-phase signal I and the quadrature signal Q. After passing through the low-pass filter and the phase detector, the phase difference between the carrier signal and the local carrier signal is obtained. The phase difference signal Control the local carrier signal NCO (numerical controlled oscillator, digitally controlled oscillator) to generate a new carrier. the

在对现有技术进行分析后，发明人发现现有技术至少具有如下缺点： After analyzing the prior art, the inventor finds that the prior art has at least the following disadvantages:

卡尔曼滤波虽然能够对高动态信号的变化趋势进行即时预测，但计算量大，计算复杂度高，在高动态环境下无法适应高速计算的要求。 Although Kalman filtering can predict the changing trend of highly dynamic signals in real time, it has a large amount of calculation and high computational complexity, and cannot meet the requirements of high-speed calculation in a highly dynamic environment. the

数字锁相环的环路带宽是固定的，不能随信噪比变化自适应调整，在载体速度突变或加速度突变的情况下会因多普勒变化率超过环路带宽而失锁。 The loop bandwidth of the digital phase-locked loop is fixed and cannot be adjusted adaptively with the change of the signal-to-noise ratio. In the case of a sudden change in the carrier speed or acceleration, the lock will be lost due to the Doppler change rate exceeding the loop bandwidth. the

发明内容Contents of the invention

本发明实施例提供了一种卡尔曼滤波、数字锁相环滤波和信号跟踪的方法和装置。所述技术方案如下： The embodiment of the present invention provides a method and device for Kalman filtering, digital phase-locked loop filtering and signal tracking. Described technical scheme is as follows:

一种卡尔曼滤波方法，包括： A Kalman filtering method, comprising:

对接收到的信号进行处理，得到接收信号，并从所述接收信号中提取观测值，所述接收信号包括接收载波和接收码； Process the received signal to obtain the received signal, and extract the observed value from the received signal, the received signal includes a received carrier and a received code;

对所述接收信号的状态值进行更新； updating the state value of the received signal;

用所述观测值修正更新后的状态值，得到当前状态的最终估计值；所述观测值通过观测方程得到， Use the observed value to correct the updated state value to obtain the final estimated value of the current state; the observed value is obtained through the observation equation,

所述观测方程如下式所示， The observation equation is shown in the following formula,

${Z Z}^{' '} ((k k)) = = [\begin{matrix} 22 {r r}_{I I} ((k k)) {r r}_{Q Q} ((k k)) \\ {r r}_{I I}^{22} ((k k)) - - {r r}_{Q Q}^{22} ((k k)) \end{matrix}] = = {A A}^{22} {d d}^{22} ((k k)) [\begin{matrix} sin sin 22 θ θ ((k k)) \\ cos cos 22 θ θ ((k k)) \end{matrix}] + + {n no}^{' '} ((k k)) = = H h ((X x ((k k)))) + + n no ((k k))$

X(k)为k时刻的状态值，r_I(k)是同相分量，r_Q(k)是正交分量，A是所述接收信号的幅值，d(k)取值±1，θ(k)＝L^TX(k)，L＝[1，0，0，0]^T，n′(k)为观测噪声矢量； X(k) is the state value at time k, r _I (k) is the in-phase component, r _Q (k) is the quadrature component, A is the amplitude of the received signal, d(k) takes a value of ±1, θ (k)=L ^T X(k), L=[1,0,0,0] ^T , n'(k) is the observation noise vector;

利用所述状态的最终估计值控制NCO产生新的信号。 The final estimate of the state is used to control the NCO to generate a new signal. the

一种利用数字锁相环滤波方法，包括： A filtering method utilizing a digital phase-locked loop, comprising:

对接收到的信号进行处理，得到接收信号，所述接收信号包括接收载波和接收码； Processing the received signal to obtain a received signal, the received signal includes a received carrier and a received code;

计算本地信号与所述接收信号之间的相位差或频率差； calculating the phase difference or frequency difference between the local signal and said received signal;

所述本地信号包括本地载波和本地码； The local signal includes a local carrier and a local code;

利用环路滤波参数对所述相位差或频率差进行环路滤波； Perform loop filtering on the phase difference or frequency difference by using loop filtering parameters;

所述环路滤波参数是利用可控根算法得到的； The loop filter parameters are obtained using a controllable root algorithm;

由所述相位差或频率差控制NCO生成新的本地信号。 The NCO is controlled by the phase difference or the frequency difference to generate a new local signal. the

一种信号跟踪的方法，包括： A method of signal tracking, comprising:

判断接收机速度、加速度或加加速度是否大于预设的阈值，如果是，则所述载体处于高动态环境，利用卡尔曼滤波进行信号跟踪；如果否，则所述载体处于非高动态环境，利用数字锁相环进行信号跟踪。 Judging whether the receiver velocity, acceleration or jerk is greater than a preset threshold, if yes, the carrier is in a high dynamic environment, use Kalman filter to perform signal tracking; if not, the carrier is in a non-high dynamic environment, use Digital phase-locked loop for signal tracking. the

所述卡尔曼滤波中的观测方程为 The observation equation in the Kalman filter is

X(k)为k时刻的状态值，r_I(k)是同相分量，r_Q(k)是正交分量，A是接收信号的幅值，d(k)取值±1，θ(k)＝L^TX(k)，L＝[1，0，0，0]^T，n′(k)为观测噪声矢量。 X(k) is the state value at time k, r _I (k) is the in-phase component, r _Q (k) is the quadrature component, A is the amplitude of the received signal, d(k) is ±1, θ(k )=L ^T X(k), L=[1, 0, 0, 0] ^T , n′(k) is the observation noise vector.

所述数字锁相环的环路滤波参数是利用可控根算法得到的。 The loop filter parameters of the digital phase-locked loop are obtained by using a controllable root algorithm. the

一种卡尔曼滤波装置，包括： A Kalman filtering device, comprising:

第一处理模块，用于对接收到的信号进行处理，得到接收信号，并从所述接收信号中提取观测值，所述接收信号包括接收载波和接收码； The first processing module is used to process the received signal, obtain the received signal, and extract the observation value from the received signal, and the received signal includes a received carrier and a received code;

更新模块，用于对所述接收信号的状态值进行更新； An update module, configured to update the state value of the received signal;

观测模块，用于用所述观测值修正更新后的状态值，得到当前状态的最终估计值；所述观测值通过观测方程得到， The observation module is used to correct the updated state value with the observed value to obtain the final estimated value of the current state; the observed value is obtained through the observation equation,

第一生成模块，用于利用所述状态的最终估计值控制NCO产生新的信号。 The first generation module is used to control the NCO to generate a new signal by using the final estimated value of the state. the

一种利用数字锁相环滤波装置，包括： A filter device utilizing a digital phase-locked loop, comprising:

第二处理模块，用于对接收到的信号进行处理，得到接收信号，所述接收信号包括接收载波和接收码； The second processing module is used to process the received signal to obtain a received signal, and the received signal includes a received carrier and a received code;

差值模块，用于计算本地信号与所述接收信号之间的相位差或频率差； difference module, used to calculate the phase difference or frequency difference between the local signal and the received signal;

环路滤波模块，用于利用环路滤波参数对所述相位差或频率差进行环路滤波； A loop filtering module, configured to perform loop filtering on the phase difference or frequency difference using loop filtering parameters;

第二生成模块，用于利用所述相位差或频率差控制NCO生成新的本地信号。 The second generating module is configured to use the phase difference or the frequency difference to control the NCO to generate a new local signal. the

一种信号跟踪的装置，包括： A signal tracking device, comprising:

处理模块，用于对接收到的信号进行处理，得到接收信号，并从所述接收信号中提取观测值，所述接收信号包括接收载波和接收码； The processing module is used to process the received signal, obtain the received signal, and extract the observation value from the received signal, and the received signal includes a received carrier and a received code;

判断模块，用于判断接收机的速度、加速度或加加速度是否大于预设的阈值，如果是，触发用于所述载体处于高动态环境，利用卡尔曼滤波进行信号跟踪的卡尔曼滤波模块；如果否，触发用于所述载体处于非高动态环境，利用数字锁相环进行信号跟踪的数字锁相环模块。 A judging module, configured to judge whether the speed, acceleration or jerk of the receiver is greater than a preset threshold, and if so, trigger a Kalman filter module for the carrier to be in a high dynamic environment and use Kalman filter for signal tracking; if No, trigger the digital phase-locked loop module used for signal tracking by using the digital phase-locked loop when the carrier is in a non-high dynamic environment. the

所述卡尔曼滤波模块中的观测方程为 The observation equation in the Kalman filtering module is

X(k)为k时刻的状态值，r_I(k)是同相分量，r_Q(k)是正交分量，A是所述接收信号的幅值，d(k)取值±1，θ(k)＝L^TX(k)，L＝[1，0，0，0]^T，n′(k)为观测噪声矢量。 X(k) is the state value at time k, r _I (k) is the in-phase component, r _Q (k) is the quadrature component, A is the amplitude of the received signal, d(k) takes a value of ±1, θ (k)=L ^T X(k), L=[1, 0, 0, 0] ^T , n′(k) is the observation noise vector.

所述数字锁相环模块的环路滤波参数是利用可控根算法得到的。 The loop filter parameters of the digital phase-locked loop module are obtained by using a controllable root algorithm. the

本发明实施例提供的技术方案的有益效果是： The beneficial effect of the technical scheme that the embodiment of the present invention provides is:

本发明通过根据载体的动态特性自适应切换的载波跟踪和码跟踪方法，当载体处于高动态环境时，接收机利用本方案提出的可自适应调整带宽的改进了观测方程的sigma点卡尔曼滤波方法进行载波跟踪；而当载体处于非高动态环境时，切换到高效率的基于连续可控根的数字锁相环进行跟踪，减小环路的误差，提高定位结果刷新率，达到在复杂动态环境中，对信号连续跟踪而不失锁的目的。 The present invention adopts the carrier tracking and code tracking method of adaptive switching according to the dynamic characteristics of the carrier. When the carrier is in a high dynamic environment, the receiver uses the improved sigma point Kalman filter of the observation equation that can adaptively adjust the bandwidth proposed by the program. method for carrier tracking; and when the carrier is in a non-high dynamic environment, switch to the high-efficiency digital phase-locked loop based on continuous controllable root for tracking, reduce the error of the loop, improve the refresh rate of positioning results, and achieve the goal of positioning in complex dynamic environments. In the environment, the purpose of continuously tracking the signal without losing the lock. the

附图说明 Description of drawings

为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。 In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. For those skilled in the art, other drawings can also be obtained according to these drawings on the premise of not paying creative efforts. the

图1是本发明实施例1提供的一种载波跟踪的方法的流程图； Fig. 1 is a flow chart of a method for carrier tracking provided by Embodiment 1 of the present invention;

图2是本发明实施例2提供的一种卡尔曼滤波的装置的结构示意图； Fig. 2 is the structural representation of the device of a kind of Kalman filter that the embodiment of the present invention 2 provides;

图3是本发明实施例2提供的一种数字锁相环滤波的装置的结构示意图； Fig. 3 is the structural representation of the device of a kind of digital phase-locked loop filtering that the embodiment of the present invention 2 provides;

图4是本发明实施例2提供的一种信号跟踪装置的结构示意图； Fig. 4 is a schematic structural diagram of a signal tracking device provided in Embodiment 2 of the present invention;

图5是本发明实施例3提供的一种码跟踪方法的流程图。 Fig. 5 is a flow chart of a code tracking method provided by Embodiment 3 of the present invention. the

具体实施方式 Detailed ways

为使本发明的目的、技术方案和优点更加清楚，下面将结合附图对本发明实施方式作进一步地详细描述。 In order to make the object, technical solution and advantages of the present invention clearer, the embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings. the

为了便于理解，这里对卡尔曼滤波进行介绍： For ease of understanding, here is an introduction to Kalman filtering:

卡尔曼滤波主要用来预估那些只能被系统本身间接或不精确观测的系统状态。卡尔曼滤波的方法具体包括： Kalman filtering is mainly used to predict the system state that can only be indirectly or imprecisely observed by the system itself. The Kalman filtering method specifically includes:

系统状态方程如下： The state equation of the system is as follows:

X_k+1＝Φ_kX_k+G_kf_k+w_k X _k+1 ＝Φ _k X _k +G _k f _k +w _k

${[\begin{matrix} {x x}_{p p} \\ {x x}_{ω ω} \\ {x x}_{a a} \\ {x x}_{t t} \end{matrix}]}_{k k + + 11} = = [\begin{matrix} 11 & {ΔT ΔT}_{k k} & \frac{{ΔT ΔT}_{k k}^{22}}{22} & 00 \\ 00 & 11 & {ΔT ΔT}_{k k} & 00 \\ 00 & 00 & 11 & 00 \\ 00 & \frac{{ΔT ΔT}_{k k}}{22 π π \times \times 15401540} & \frac{{ΔT ΔT}_{k k}^{22}}{44 π π \times \times 15401540} & 11 \end{matrix}] {[\begin{matrix} {x x}_{p p} \\ {x x}_{ω ω} \\ {x x}_{a a} \\ {x x}_{t t} \end{matrix}]}_{k k} + + [\begin{matrix} - - {ΔT ΔT}_{k k} & 00 \\ 00 & 00 \\ 00 & 00 \\ 00 & - - {ΔT ΔT}_{k k} \end{matrix}] {[\begin{matrix} {ω ω}_{Ncok Ncok} \\ {f f}_{ck ck} \end{matrix}]}_{k k} + + {w w}_{k k}$

上式是推导建立的4阶线性状态方程，所选状态向量前三个是关于载波的，另一个是关于C/A码的。其中，x_p是真实载波和本地复现载波的相位差； $x_{ω} = \overset{\cdot}{x_{p}}$ 是载波的多普勒漂移； $x_{a} = \overset{\cdot}{x_{ω}}$ 是载波的多普勒漂移变化率；x_t是真实码相位同本地复现码相位的差，单位是C/A码基码个数；ΔT_k是两次计算的时间差；k表示第几次测量；ω_Ncok是本地载波复现时在中频基础上的角频率偏移；f_ck是本地接收机复现C/A码时，码速率在1.023MHz基础上的偏移；w_k是4×1过程噪声矢量，主要包含了卫星和接收机相对运动的影响，由电离层波动引起的码和载波之间不同步的噪声。另外，方程中参数1540是L1载波与C/A码频率之比。 The above formula is a 4th-order linear state equation derived and established. The first three of the selected state vectors are related to the carrier, and the other is related to the C/A code. Among them, x _p is the phase difference between the real carrier and the local reproduced carrier; $x_{ω} = \overset{&Center Dot;}{x_{p}}$ is the Doppler shift of the carrier; $x_{a} = \overset{\cdot}{x_{ω}}$ is the Doppler shift rate of the carrier; x _t is the difference between the real code phase and the local reproduced code phase, and the unit is the number of C/A code base codes; ΔT _k is the time difference between two calculations; k represents the number of times Measurement; ω _Ncok is the angular frequency offset based on the intermediate frequency when the local carrier reproduces; f _ck is the offset of the code rate based on 1.023MHz when the local receiver reproduces the C/A code; w _k is 4×1 The process noise vector mainly includes the influence of the relative motion of the satellite and the receiver, and the asynchronous noise between the code and the carrier caused by ionospheric fluctuations. Additionally, the parameter 1540 in the equation is the ratio of L1 carrier to C/A code frequency.

系统的观测方程如下： The observation equation of the system is as follows:

Z_k＝H_kX_k+U_kf_k+v_k Z _k ＝H _k X _k +U _k f _k +v _k

${\overset{^^}{Z Z}}_{k k} = = [\begin{matrix} Δ Δ {\overset{^^}{φ φ}}_{k k} \\ Δ Δ {\overset{^^}{τ τ}}_{k k} \end{matrix}] = = [\begin{matrix} 11 & \frac{Δ Δ {T T}_{k k}}{22} & \frac{{ΔT ΔT}_{k k}^{22}}{66} & 00 \\ 00 & \frac{{ΔT ΔT}_{k k}}{44 π π \times \times 15401540} & \frac{{ΔT ΔT}_{k k}^{22}}{1212 π π \times \times 15401540} & 11 \end{matrix}] {[\begin{matrix} {x x}_{p p} \\ {x x}_{ω ω} \\ {x x}_{a a} \\ {x x}_{t t} \end{matrix}]}_{k k} + + [\begin{matrix} - - \frac{{ΔT ΔT}_{k k}}{22} & 00 \\ 00 & - - \frac{{ΔT ΔT}_{k k}}{22} \end{matrix}] {[\begin{matrix} {ω ω}_{Ncok Ncok} \\ {f f}_{ck ck} \end{matrix}]}_{k k} + + {v v}_{k k}$

上式是推导建立的系统观测方程，观测量是Δφ_k和Δτ_k。Δφ_k是第k次预检测积分时间ΔT_k内，真实载波和本地复现载波的平均相位差；Δτ_k是第k次预检测积分时间ΔT_k内，真实C/A码同本地复现码的平均相位差，单位是基码个数。v_k是2×1观测噪声矢量。实际观测量来自于环路鉴别器的输出： The above formula is the system observation equation derived and established, and the observation quantities are Δφ _k and Δτ _k . Δφ _k is the average phase difference between the real carrier and the local reproduced carrier within _the k-th _pre -detection integration time ΔT _k ; The average phase difference of , the unit is the number of base codes. v _k is a 2×1 observation noise vector. The actual observations come from the output of the loop discriminator:

$Δ Δ {\overset{~ ~}{φ φ}}_{k k} = = arctan arctan [[{Q Q}_{Pk Pk} / / {I I}_{Pk Pk}]]$

其中，I_Ek、I_Pk、I_Lk、Q_Ek、Q_Pk、Q_Lk分别是I、Q支路第k次预检测积分的超前、即时、滞后值。 Among them, I _Ek , I _Pk , I _Lk , Q _Ek , Q _Pk , and Q _Lk are the leading, immediate, and lagging values of the k-th pre-detection integration of the I and Q branches, respectively.

环路滤波过程如下： The loop filtering process is as follows:

${\overset{^^}{X x}}_{k k,, k k - - 11} = = {Φ Φ}_{k k,, k k - - 11} {\overset{^^}{X x}}_{k k - - 11,, k k - - 11} + + {G G}_{k k,, k k - - 11} {\overset{^^}{f f}}_{k k - - 11}$

${P P}_{k k,, k k - - 11} = = {Φ Φ}_{k k,, k k - - 11} {P P}_{k k - - 11} {Φ Φ}_{k k,, k k - - 11}^{T T} + + {\overset{^^}{Q Q}}_{k k - - 11}$

${J J}_{k k} = = {P P}_{k k,, k k - - 11} {H h}_{k k}^{T T} {[[{H h}_{k k} {P P}_{k k,, k k - - 11} {H h}_{k k}^{T T} + + {\overset{^^}{R R}}_{k k - - 11}]]}^{- - 11}$

${\overset{^^}{X x}}_{k k} = = {\overset{^^}{X x}}_{k k,, k k - - 11} + + {J J}_{k k} [[{Z Z}_{k k} - - {H h}_{k k} {\overset{^^}{X x}}_{k k,, k k - - 11} - - {U u}_{k k} {\overset{^^}{f f}}_{k k - - 11}]]$

P_k＝[I-J_kH_k]P_k，k-1 P _k = [IJ _k H _k ] P _{k, k-1}

其中， $E {w_{k} w_{l}^{T}} = Q_{k} δ_{k, l},$ $E {v_{k} v_{l}^{T}} = R_{k} δ_{k, l},$ 且 $E {w_{k} v_{l}^{T}} = 0 .$ in, $E. {w_{k} w_{l}^{T}} = Q_{k} δ_{k, l},$ $E. {v_{k} v_{l}^{T}} = R_{k} δ_{k, l},$ and $E. {w_{k} v_{l}^{T}} = 0 .$

普通卡尔曼滤波器用于估计线性系统的状态，对于非线性系统的状态，则应使用扩展卡尔曼滤波器进行估计，接下来详细叙述扩展卡尔曼(EKF)的算法原理： The ordinary Kalman filter is used to estimate the state of the linear system. For the state of the nonlinear system, the extended Kalman filter should be used for estimation. Next, the algorithm principle of the extended Kalman (EKF) is described in detail:

我们以GPS卫星为例，接收到的数字中频信号如下式： We take GPS satellite as an example, the received digital intermediate frequency signal is as follows:

r(k)＝Ad(k)c[(1+ζ)(k-τ)]cos(ω_ck+φ₀)+n(k) r(k)=Ad(k)c[(1+ζ)(k-τ)]cos(ω _c k+φ ₀ )+n(k)

当环路积分时间为T_s时，载波相位θ(k)可按如下式展开： When the loop integration time is T _s , the carrier phase θ(k) can be expanded as follows:

$θ θ ((k k + + 11)) = = θ θ ((k k)) + + {T T}_{s the s} {ω ω}_{00} ((k k)) + + {T T}_{s the s}^{22} {ω ω}_{11} ((k k)) / / 22 + + {T T}_{s the s}^{33} {ω ω}_{22} ((k k)) / / 66 + + {η η}_{11} ((k k))$

${ω ω}_{00} ((k k + + 11)) = = {ω ω}_{00} ((k k)) + + {T T}_{s the s} {ω ω}_{11} ((k k)) + + {T T}_{s the s}^{22} {ω ω}_{22} ((k k)) / / 22 + + {η η}_{22} ((k k))$

ω₁(k+1)＝ω₁(k)+T_sω₂(k)+η₃(k) ω ₁ (k+1)=ω ₁ (k)+T _s ω ₂ (k)+η ₃ (k)

ω₂(k+1)＝ω₂(k)+η₄(k) ω ₂ (k+1) = ω ₂ (k) + η ₄ (k)

其中ω₀(k)，ω₁(k)，ω₂(k)是载波相位的各阶导数，分别表示频率、频率的变化率和频率的二阶导数，η_i(i＝1，2，3，4)为展开式余项，表示策动噪声。由于对频率估计的同时估计相位，可降低频率估计误差，同时也为适合高动态环境的需要，将频率一、二阶导数进行一起估计，则状态向量表示为： Wherein ω ₀ (k), ω ₁ (k), ω ₂ (k) are the derivatives of each order of the carrier phase, respectively representing the frequency, the rate of change of the frequency and the second order derivative of the frequency, η _i (i=1, 2, 3, 4) is the remainder of the expansion, which represents the driving noise. Since the phase is estimated at the same time as the frequency estimation, the frequency estimation error can be reduced. At the same time, to meet the needs of a high dynamic environment, the first and second order derivatives of the frequency are estimated together, and the state vector is expressed as:

X(k)＝[θ(k)，ω₀(k)，ω₁(k)，ω₂(k)]^T X(k)=[θ(k), ω ₀ (k), ω ₁ (k), ω ₂ (k)] ^T

可得状态方程如式所示， The state equation can be obtained as shown in the formula,

X(k+1)＝ФX(k)+η(k) X(k+1)＝ФX(k)+η(k)

其中，η(k)＝[η₁(k)，η₂(k)，η₃(k)，η₄(k)]^T是策动噪声矢量，一般认为是高斯白噪声，系统转移矩阵Φ和η(k)的协方差矩阵Q可以分别表示为， Among them, η(k)=[η ₁ (k), η ₂ (k), η ₃ (k), η ₄ (k)] ^T is the driving noise vector, generally considered to be Gaussian white noise, the system transfer matrix Φ and The covariance matrix Q of η(k) can be expressed as,

$Φ Φ = = [\begin{matrix} 11 & {T T}_{s the s} & {T T}_{s the s}^{22} / / 22 & {T T}_{s the s}^{33} / / 66 \\ 00 & 11 & {T T}_{s the s} & {T T}_{s the s}^{22} / / 22 \\ 00 & 00 & 11 & {T T}_{s the s} \\ 00 & 00 & 00 & 11 \end{matrix}]$

$Q Q = = {qT wxya}_{s the s} [\begin{matrix} {T T}_{s the s}^{66} / / 252252 & {T T}_{s the s}^{22} / / 7272 & {T T}_{s the s}^{44} / / 3030 & {T T}_{s the s}^{33} / / 24 twenty four \\ {T T}_{s the s}^{55} / / 7272 & {T T}_{s the s}^{44} / / 2020 & {T T}_{s the s}^{33} / / 88 & {T T}_{s the s}^{22} / / 66 \\ {T T}_{s the s}^{44} / / 3030 & {T T}_{s the s}^{33} / / 88 & {T T}_{s the s}^{22} / / 33 & {T T}_{s the s} / / 22 \\ {T T}_{s the s}^{33} / / 24 twenty four & {T T}_{s the s}^{22} / / 66 & {T T}_{s the s} / / 22 & 11 \end{matrix}]$

数字中频信号经过解扩与正交分解之后，第k次输入载波跟踪的即时信号可以表示为： After the digital intermediate frequency signal is despread and orthogonally decomposed, the real-time signal of the kth input carrier tracking can be expressed as:

r_I(k)＝Ad(k)sin(θ(k))+n_I(k) r _I (k) = Ad (k) sin (θ (k)) + n _I (k)

r_Q(k)＝Ad(k)cos(θ(k))+n_Q(k) r _Q (k) = Ad (k) cos (θ (k)) + n _Q (k)

其中，r_I(k)是同相分量，r_Q(k)是正交分量，d(k)取值±1，θ(k)＝L^TX(k)，L＝[1，0，0，0]^T，n_I(k)，n_Q(k)为观测噪声矢量。就GPS C/A而言，通常将上式表示为： Among them, r _I (k) is the in-phase component, r _Q (k) is the quadrature component, d (k) takes the value of ± 1, θ (k) = L ^T X (k), L = [1, 0, 0 , 0] ^T , n _I (k), n _Q (k) are observation noise vectors. As far as GPS C/A is concerned, the above formula is usually expressed as:

$Z Z ((k k)) = = [\begin{matrix} {r r}_{I I} ((k k)) \\ {r r}_{Q Q} ((k k)) \end{matrix}] = = Ad ad ((k k)) [\begin{matrix} sin sin ((θ θ ((k k)))) \\ cos cos ((θ θ ((k k)))) \end{matrix}] + + n no ((k k))$

上式为扩展卡尔曼滤波的观测方程。 The above formula is the observation equation of extended Kalman filter. the

其中，n(k)＝[n_I(k)，n_Q(k))]^T为观测矢量噪声，其协方差阵为

σ_{n}^{2} = N_{0} / ({2 T}_{s}),

I表示2×2的单位阵。 Among them, n(k)=[n _I (k), n _Q (k))] ^T is the observation vector noise, and its covariance matrix is

σ_{no}^{2} = N_{0} / ({2 T}_{the s}),

I represents a 2×2 unit matrix.

再利用该观测方程和与状态值得到观测值，从观测值中提取出本地载波与接收载波的相位差，利用该相位差控制载波NCO产生新的载波。 Then use the observation equation and the state value to obtain the observation value, extract the phase difference between the local carrier and the receiving carrier from the observation value, and use the phase difference to control the carrier NCO to generate a new carrier. the

实施例1 Example 1

为了适应复杂的动态环境，使跟踪环路能够根据动态环境的变化切换载波跟踪方法，环路带宽具有一定的自适应调整能力，在高动态环境中具有较宽的带宽，在非高动态环境中具有较小的带宽，并兼顾环路的捕获性能和稳态的跟踪性能，本发明实施例提供了一种卡尔曼滤波方法，包括： In order to adapt to the complex dynamic environment, so that the tracking loop can switch the carrier tracking method according to the change of the dynamic environment, the loop bandwidth has a certain ability of self-adaptive adjustment, it has a wider bandwidth in the high dynamic environment, and in the non-high dynamic environment With a smaller bandwidth, and taking into account the acquisition performance of the loop and the tracking performance of the steady state, the embodiment of the present invention provides a Kalman filtering method, including:

对接收到的信号进行处理，得到接收信号，并从该接收信号中提取观测值，该接收信号包括接收载波和接收码； Process the received signal to obtain the received signal, and extract the observation value from the received signal, the received signal includes the received carrier and the received code;

其中，提取观测值的方法有多种，本发明实施例不做具体限定。 There are multiple methods for extracting observed values, which are not specifically limited in this embodiment of the present invention. the

对该接收信号的状态值进行更新； Update the state value of the received signal;

用该观测值修正更新后的状态值，得到当前状态的最终估计值；该观测值通过观测方程得到， Use the observed value to correct the updated state value to obtain the final estimated value of the current state; the observed value is obtained through the observation equation,

该观测方程如下式所示， The observation equation is shown in the following formula,

X(k)为k时刻的状态值，r_I(k)是同相分量，r_Q(k)是正交分量，A是该接收信号的幅值，d(k)取值±1，θ(k)＝L^TX(k)，L＝[1，0，0，0]^T，n′(k)为观测噪声矢量； X(k) is the state value at time k, r _I (k) is the in-phase component, r _Q (k) is the quadrature component, A is the amplitude of the received signal, d(k) is ±1, θ( k)=L ^T X(k), L=[1,0,0,0] ^T , n'(k) is the observation noise vector;

利用该状态的最终估计值控制NCO产生新的信号。 The final estimate of the state is used to control the NCO to generate a new signal. the

本发明实施例提供了一种利用数字锁相环滤波方法，包括： Embodiments of the present invention provide a filtering method using a digital phase-locked loop, including:

对接收到的信号进行处理，得到接收信号，该接收信号包括接收载波和接收码； Process the received signal to obtain a received signal, which includes a received carrier and a received code;

计算本地信号与该接收信号之间的相位差或频率差； Calculate the phase difference or frequency difference between the local signal and the received signal;

该本地信号包括本地载波和本地码； The local signal includes a local carrier and a local code;

利用环路滤波参数对该相位差或频率差进行环路滤波； Loop filtering is performed on the phase difference or frequency difference by using the loop filtering parameters;

该环路滤波参数是利用可控根算法得到的； The loop filter parameters are obtained by using the controllable root algorithm;

由该相位差或频率差控制NCO生成新的本地信号。 The NCO is controlled by this phase difference or frequency difference to generate a new local signal. the

本发明实施例还提供了一种信号跟踪的方法，包括： The embodiment of the present invention also provides a method for signal tracking, including:

判断接收机速度、加速度或加加速度是否大于预设的阈值，如果是，则该载体处于高动态环境，利用卡尔曼滤波进行信号跟踪；如果否，则该载体处于非高动态环境，利用数字锁相环进行信号跟踪。 Determine whether the receiver speed, acceleration or jerk is greater than the preset threshold, if yes, the carrier is in a high dynamic environment, use Kalman filter for signal tracking; if not, the carrier is in a non-high dynamic environment, use digital lock Phase loop for signal tracking. the

该卡尔曼滤波中的观测方程为 The observation equation in this Kalman filter is

该数字锁相环的环路滤波参数是利用可控根算法得到的。 The loop filter parameters of the digital phase-locked loop are obtained by using the controllable root algorithm. the

优选的，本发明实施例提供了一种载波跟踪的方法，参见图1，该方法具体包括： Preferably, the embodiment of the present invention provides a method for carrier tracking, referring to Fig. 1, the method specifically includes:

101：接收机接收卫星信号，通过射频前端、A/D转换，将接收到的卫星信号下变频到中频信号(4Mbps)，并对该中频信号数字化，得到中频数字信号即接收信号；将中频数字信号与本地产生的C/A码相乘，乘以本地载波的同相与正交分量，得到I、Q路信号，即观测信号，并从观测信号中提取当前的观测值； 101: The receiver receives the satellite signal, down-converts the received satellite signal to an intermediate frequency signal (4Mbps) through the RF front-end and A/D conversion, and digitizes the intermediate frequency signal to obtain the intermediate frequency digital signal, that is, the received signal; the intermediate frequency digital signal The signal is multiplied by the C/A code generated locally, and multiplied by the in-phase and quadrature components of the local carrier to obtain the I and Q signal, that is, the observation signal, and extract the current observation value from the observation signal;

需要说明的是，当进行码跟踪时，得到中频数字信号后，将中频数字信号与本地载波的同相和正交分量分别相乘，再乘以本地产生的C/A码，得到观测信号，并从观测信号中提取当前的观测值。 It should be noted that when performing code tracking, after obtaining the IF digital signal, the IF digital signal is multiplied by the in-phase and quadrature components of the local carrier, and then multiplied by the locally generated C/A code to obtain the observed signal, and Extract the current observation from the observation signal. the

其中，接收信号包括但不限于从信号中提取的接收载波。在本实施例中，将载波跟踪方法和码跟踪方法统称为信号跟踪方法。 Wherein, the received signal includes but not limited to the received carrier extracted from the signal. In this embodiment, the carrier tracking method and the code tracking method are collectively referred to as the signal tracking method. the

102：判断接收机的速度、加速度或加加速度是否大于预设阈值，如果是，则接收机处于高动态，执行步骤103，如果否，接收机处于非高动态，执行步骤106； 102: Judging whether the speed, acceleration or jerk of the receiver is greater than the preset threshold, if yes, the receiver is in high dynamic state, go to step 103, if not, the receiver is in non-high dynamic state, go to step 106;

其中，判断接收机的运动特性即是判断信号的载体的运动特性，因为定位是给接收机进行定位，或接收芯片，该接收机或芯片可嵌入到任何运动中的载体上，所以给接收机定位也就是给运动载体定位。 Among them, judging the motion characteristics of the receiver is to judge the motion characteristics of the carrier of the signal, because the positioning is to locate the receiver, or the receiving chip, the receiver or chip can be embedded in any moving carrier, so for the receiver Positioning is to locate the motion carrier. the

其中，对接收机动态特性的判断是通过接收机自带的传感器(加速度计或陀螺仪等)的信息，包括但不限于速度、加速度或加加速度等进行的。 Wherein, the judgment of the dynamic characteristic of the receiver is carried out through the information of the sensor (accelerometer or gyroscope, etc.) provided by the receiver, including but not limited to velocity, acceleration or jerk. the

其中，上述阈值可以根据实际情况进行设定，本发明实施例不做具体限定。 Wherein, the foregoing threshold may be set according to actual conditions, and is not specifically limited in this embodiment of the present invention. the

103：对接收信号中的各状态值(载波相位、频率、频率的一、二阶导数)进行更新； 103: Update each state value (carrier phase, frequency, first and second derivatives of frequency) in the received signal;

具体地，下述103b-103b的过程为对接收信号中各状态值进行更新的过程，该过程具体包括： Specifically, the following 103b-103b process is a process of updating each state value in the received signal, and the process specifically includes:

103a：对接收信号进行初始化，给定初始状态估计值

与初始估计协方差阵S_0|0； 103a: Initialize the received signal and give the initial state estimation value

and the initial estimated covariance matrix S _0|0 ;

其中，初始化的对象是接收信号的初始状态估计值和初始估计协方差阵，初始状态估计值是4*1矩阵，值均为0，协方差矩阵为 $Q = {qT}_{s} [\begin{matrix} T_{s}^{6} / 252 & T_{s}^{5} / 72 & T_{s}^{4} / 30 & T_{s}^{3} / 24 \\ T_{s}^{5} / 72 & T_{s}^{4} / 20 & T_{s}^{3} / 8 & T_{s}^{2} / 6 \\ T_{s}^{4} / 30 & T_{s}^{3} / 8 & T_{s}^{2} / 3 & T_{s} / 2 \\ T_{s}^{3} / 24 & T_{s}^{2} / 6 & T_{s} / 2 & 1 \end{matrix}],$ Ts为预检测积分时间，本发明实施例中Ts为1ms，q取1000。 Among them, the object of initialization is the initial state estimation value and the initial estimation covariance matrix of the received signal, the initial state estimation value is a 4*1 matrix, the values are all 0, and the covariance matrix is $Q = {wxya}_{the s} [\begin{matrix} T_{the s}^{6} / 252 & T_{the s}^{5} / 72 & T_{the s}^{4} / 30 & T_{the s}^{3} / twenty four \\ T_{the s}^{5} / 72 & T_{the s}^{4} / 20 & T_{the s}^{3} / 8 & T_{the s}^{2} / 6 \\ T_{the s}^{4} / 30 & T_{the s}^{3} / 8 & T_{the s}^{2} / 3 & T_{the s} / 2 \\ T_{the s}^{3} / twenty four & T_{the s}^{2} / 6 & T_{the s} / 2 & 1 \end{matrix}],$ Ts is the pre-detection integration time. In the embodiment of the present invention, Ts is 1 ms, and q is 1000.

103b：确定sigma点集和状态更新； 103b: determine the sigma point set and update the state;

其中，确定sigma点集是一个数学建模过程，通过加权统计线性回归方法得到，具体包括：根据随机变量先验分布选取多个点，利用非线性函数计算这些点的值，然后利用线性回归技术实现对随机变量非线性函数的线性化，其中选取的多个回归点就是sigma点，也即确定了sigma点集。 Among them, determining the sigma point set is a mathematical modeling process, which is obtained by weighted statistical linear regression method, which specifically includes: selecting multiple points according to the prior distribution of random variables, using nonlinear functions to calculate the values of these points, and then using linear regression technology The linearization of the nonlinear function of the random variable is realized, and the multiple regression points selected are the sigma points, that is, the sigma point set is determined. the

其中，状态更新的对象是接收信号的载波相位、频率以及频率的一、二阶导数，该状态更新的具体为：用k时刻的状态x_k基于全局的估计值和估计误差的协方差的平方根S_k|k产生2n+1个σ点，计算状态的一步预测值

和预测误差协方差的平方根S_k+1|k，其算法详见以下公式： Among them, the object of the state update is the carrier phase, frequency and the first and second order derivatives of the frequency of the received signal. The specific state update is: the state x _k at time k is based on the global estimated value and the square root S _k|k of the covariance of the estimation error to generate 2n+1 σ points, and calculate the one-step predicted value of the state

and the square root S _k+1|k of the forecast error covariance, the algorithm is detailed in the following formula:

${X x}_{k k} = = [[{\overset{^^}{X x}}_{k k},, {\overset{^^}{X x}}_{k k} + + \sqrt{n no + + r r} {S S}_{k k},, {\overset{^^}{X x}}_{k k} - - \sqrt{n no + + k k} {S S}_{k k}]]$

X_k+1|k＝Φ(X_k) X _k+1|k ＝Φ(X _k )

λ＝α²(n+k)-n λ=α ² (n+k)-n

${W W}_{00}^{((m m))} = = λ λ / / ((n no + + λ λ))$

${W W}_{00}^{((c c))} = = λ λ / / ((n no + + λ λ)) + + ((11 - - {α α}^{22} + + β β))$

${W W}_{i i}^{m m} = = {W W}_{i i}^{c c} = = 11 / / [[22 ((n no + + λ λ))]],, i i = = 1,2 1,2,, . . . . . . 22 n no$

${\overset{^^}{X x}}_{k k + + 11 | | k k} = = {Σ Σ}_{i i = = 00}^{22 n no} {W W}_{i i}^{((m m))} {X x}_{i i,, k k + + 11 | | k k}$

${S S}_{k k + + 11 | | k k}^{00} = = qr qr {{[[\sqrt{{W W}_{11}^{c c}} (({X x}_{11 : : 22 n no,, k k + + 11 | | k k} - - {\overset{^^}{X x}}_{k k + + 11 | | k k})),, \sqrt{Q Q}]]}}$

${S S}_{k k + + 11 | | k k} = = choludate choludate (({S S}_{k k + + 11 | | k k}^{00},, {X x}_{00,, k k} - - {\overset{^^}{X x}}_{k k + + 11 | | k k},, {W W}_{00}^{c c}))$

需要说明的是，上述的状态更新对应时刻k的状态，当时刻k+1时，进入下一轮的状态更新。 It should be noted that the above state update corresponds to the state at time k, and when time k+1, enters the next round of state update. the

104：用观测值修正更新后的状态值，得到当前状态的最终估计值； 104: Correct the updated state value with the observed value to obtain the final estimated value of the current state;

具体地，步骤104是测量更新的过程，用Z_k+1对

进行修正，得到k+1时刻基于量测信息Z^k及观测值Z_k+1状态的最终估计值

以及相应的估计误差的平方根S_k+1|k+1。 Specifically, step 104 is the process of measurement update, using Z _k+1 to

Make corrections to obtain the final estimated value based on the measurement information Z ^k and the observed value Z _k+1 state at k+1 time

and the corresponding square root of the estimation error S _k+1|k+1 .

具体地，用z_k+1 ¹对

进行修正，得到k+1时刻基于量测z^k及观测值z_k+1 ¹状态的最终估计值

以及相应的估计误差的平方根S_k+1|k+1 ¹。用z_k+1 ²对

进行修正，得到k+1时刻基于量测z^k及观测值z_k+1 ¹，z_k+1 ²状态的最终估计值以及相应的估计误差的平方根S_k+1|k+1 ²。用z_k+1 ⁱ(3≤i≤N)对

进行修正，得到k+1时刻基于量测z^k及观测值z_k+1 ¹，z_k+1 ²，...，z_k+1 ⁱ状态的最终估计值

以及相应的估计误差的平方根S_k+1|k+1 ⁱ。 Specifically, use z _k+1 ¹ pair

Make corrections to obtain the final estimated value based on the measurement z ^k and the observed value z _k+1 ¹ state at time k+1

and the corresponding square root of the estimation error S _k+1|k+1 ¹ . Use z _k+1 ² pairs

Make corrections to obtain the final estimated value based on the measurement z ^k and the observed value z _k+1 ¹ , z _k+1 ² state at time k+1 and the corresponding square root of the estimation error S _k+1|k+1 ² . Use z _k+1 ⁱ (3≤i≤N) to

Make corrections to obtain the final estimated value based on the measurement z ^k and observed values z _k+1 ¹ , z _k+1 ² ,..., z _k+1 ⁱ state at time k+1

and the corresponding square root of the estimation error S _k+1|k+1 ⁱ .

最终得到系统在k+1时刻基于量测信息z^k+1状态的最终估计值和相应的估计误差为： Finally, the final estimated value of the system based on the measurement information z ^k+1 state at time k+1 and the corresponding estimated error are:

${\overset{^^}{x x}}_{k k + + 11 | | k k + + 11} = = {\overset{^^}{x x}}_{k k + + 11 | | k k + + 11}^{N N}$

${\overset{^^}{P P}}_{k k + + 11 | | k k + + 11} = = {(({S S}_{k k + + 11 | | k k + + 11}^{N N}))}^{T T} {S S}_{k k + + 11 | | k k + + 11}^{N N}$

具体算法如下式所示： The specific algorithm is as follows:

${S S}_{k k + + 11 | | k k} = = choludate choludate (({S S}_{k k + + 11 | | k k}^{00},, {y the y}_{00,, k k + + 11 | | k k} - - {Z Z}_{k k + + 11 | | k k},, {W W}_{00}^{((c c))}))$

y_k+1|k＝H(X_k+1|k) y _k+1|k ＝H(X _k+1|k )

${Z Z}_{k k + + 11 | | k k} = = {Σ Σ}_{i i = = 00}^{22 n no} {W W}_{i i}^{((m m))} {y the y}_{i i,, k k + + 11 | | k k}$

${P P}_{xy xy ((k k + + 11 | | k k))} = = {Σ Σ}_{i i = = 00}^{22 n no} {W W}_{i i}^{((c c))} [[{X x}_{i i,, k k + + 11 | | k k} - - {\overset{^^}{X x}}_{k k + + 11 | | k k}]] {[[{y the y}_{i i,, k k + + 11 | | k k} - - {Z Z}_{k k + + 11 | | k k}]]}^{T T}$

${K K}_{k k + + 11} = = (({P P}_{xy xy ((k k + + 11 | | k k))} / / {S S}_{y the y ((k k + + 11 / / k k))}^{T T})) / / {S S}_{y the y ((k k + + 11 | | k k))}$

${\overset{^^}{X x}}_{k k + + 11 | | k k + + 11} = = {\overset{^^}{X x}}_{k k + + 11 | | k k} + + {K K}_{k k + + 11} (({Z Z}_{k k + + 11} - - {Z Z}_{k k + + 11 | | k k}))$

U＝K_k+1S_y(k+1|k) U＝K _k+1 S _y(k+1|k)

S_k+1|k+1＝choludate(S_k+1|k，U，-1) S _k+1|k+1 ＝choludate(S _k+1|k ，U，-1)

其中，上面式中α决定sigma点围绕均值的散布，通常取一小正数(如：1e-4≤α≤11)，k为比例因数，一般在状态估计时设为0，β是另一比例因子，用来合并随机变量分布的先验知识(对于高斯分布，其最优值为2)，qr{}表示矩阵的QR分解，cholupdate{}表示矩阵Cholesky分解的修正，即若S为原始矩阵P的Cholesky分解，修正矩阵的Cholesky分解为S＝cholupdate{S，u，±v}。 Among them, α in the above formula determines the distribution of sigma points around the mean value, usually a small positive number (such as: 1e-4≤α≤11), k is a scaling factor, generally set to 0 in state estimation, and β is another Scale factor, used to combine prior knowledge of random variable distribution (for Gaussian distribution, the optimal value is 2), qr{} represents the QR decomposition of the matrix, cholupdate{} represents the correction of the Cholesky decomposition of the matrix, that is, if S is the original Cholesky decomposition of matrix P, modified matrix The Cholesky decomposition of S=cholupdate{S,u,±v}.

具体地，在本实施例中，Z_k+1|k是通过以下观测方程获取的， Specifically, in this embodiment, Z _k+1|k is obtained through the following observation equation,

${Z Z}_{k k + + 11 | | k k} = = [\begin{matrix} 22 {r r}_{I I} ((k k)) {r r}_{Q Q} ((k k)) \\ {r r}_{I I}^{22} ((k k)) - - {r r}_{Q Q}^{22} ((k k)) \end{matrix}] = = {A A}^{22} {d d}^{22} ((k k)) [\begin{matrix} sin sin 22 θ θ ((k k)) \\ cos cos 22 θ θ ((k k)) \end{matrix}] + + {n no}^{' '} ((k k)) = = H h ((X x ((k k)))) + + n no ((k k))$

n′(k)为观测噪声矢量，通过d(k)的平方d²(k)来去掉数据跳变的影响。 n′(k) is the observation noise vector, and the influence of data jump is removed by the square d ² (k) of d(k).

X(k)为k时刻的状态值，r_I(k)是同相分量，r_Q(k)是正交分量，d(k)取值±1，θ(k)＝L^TX(k)，L＝[1，0，0，0]^T，A是接收信号的幅值； X(k) is the state value at time k, r _I (k) is the in-phase component, r _Q (k) is the quadrature component, d(k) is ±1, θ(k)=L ^T X(k) , L=[1,0,0,0] ^T , A is the amplitude of the received signal;

其中，该观测方程是由 $Z (k) = [\begin{matrix} r_{I} (k) \\ r_{Q} (k) \end{matrix}] = Ad (k) [\begin{matrix} \sin (θ (k)) \\ \cos (θ (k)) \end{matrix}] + n (k)$ 和三角函数倍角公式sin2A＝2sinAcosA与cos2A＝(cosA)²-(sinA)²得到的； Among them, the observation equation is given by $Z (k) = [\begin{matrix} r_{I} (k) \\ r_{Q} (k) \end{matrix}] = ad (k) [\begin{matrix} \sin (θ (k)) \\ \cos (θ (k)) \end{matrix}] + no (k)$ And trigonometric function double angle formula sin2A=2sinAcosA and cos2A=(cosA) ² -(sinA) ² obtains;

其中，r_I(k)是同相分量，r_Q(k)是正交分量，d(k)取值±1，θ(k)＝L^TX(k)，L＝[1，0，0，0]^T，n_I(k)，n_Q(k)为观测噪声矢量。 Among them, r _I (k) is the in-phase component, r _Q (k) is the quadrature component, d (k) takes the value of ± 1, θ (k) = L ^T X (k), L = [1, 0, 0 , 0] ^T , n _I (k), n _Q (k) are observation noise vectors.

105：利用当前状态的最终估计值控制载波NCO产生新的载波，结束。 105: Use the final estimated value of the current state to control the carrier NCO to generate a new carrier, and end. the

具体地，当前状态值包括但不限于θ(k+1)，利用θ(k+1)控制载波NCO产生新的载波。 Specifically, the current state value includes but not limited to θ(k+1), and θ(k+1) is used to control the carrier NCO to generate a new carrier. the

上述步骤103-105是通过上一次的状态值和本次的观测值来预测本次的状态值的过程，该过程的基本思想是：根据已知k时刻状态x_k基于全局的估计值

及相应估计误差的协方差P_k|k，在k+1时刻，利用滤波器和k+1时刻各传感器的观测值依次对状态x_k+1进行估计，最后得到基于全局的信息的估计值

和相应误差的协方差P_k+1|k+1。 The above steps 103-105 are the process of predicting the state value of this time through the state value of the last time and the observed value of this time. The basic idea of this process is: according to the estimated value of the state x _k based on the global at known k time

and the covariance P _k|k of the corresponding estimation error, at time k+1, use the filter and the observation values of each sensor at time k+1 to estimate the state x _k+1 in turn, and finally get the estimated value based on the global information

and the covariance P _k+1|k+1 of the corresponding error.

需要说明的是，上述步骤103-105是利用可自适应调整带宽的改进sigma点卡尔曼滤波环路进行载波跟踪的过程，但是由于接收机所处的复杂动态环境，在该跟踪过程后仍需对接收机的动态特性进行判断，根据判断结果，选择跟踪方法。 It should be noted that the above steps 103-105 are the process of carrier tracking using the improved sigma point Kalman filter loop which can adaptively adjust the bandwidth, but due to the complex dynamic environment in which the receiver is located, it is still necessary to The dynamic characteristics of the receiver are judged, and the tracking method is selected according to the judgment result. the

需要说明的是，跟踪的目的是为了使本地产生的载波与码相位都能与实际接收信号完全对应，从而实现精确剥离。 It should be noted that the purpose of tracking is to make the locally generated carrier and code phase completely correspond to the actual received signal, so as to achieve precise stripping. the

106：接收信号首先进入到鉴相器(鉴频器)，计算出本地载波与接收载波之间的相位(或频率)差； 106: The received signal first enters the phase detector (frequency detector), and calculates the phase (or frequency) difference between the local carrier and the received carrier;

107：利用环路滤波参数对该相位(或频率)差进行环路滤波； 107: Perform loop filtering on the phase (or frequency) difference by using loop filtering parameters;

其中，环路滤波的作用是滤除该差值中的杂波及噪声等，只保留有效部分。 Among them, the function of the loop filter is to filter out the clutter and noise in the difference, and only keep the effective part. the

其中，上述环路滤波参数由可控根算法确定，为了解决模拟环路来设计数字环路的方法中的问题，STEPENS S.A.和THOMASJ.B.提出设计DPLL(DigitalPLL，全数字锁相环)的可控根公式，该组公式给出了B_nT＜0.1的连续更新(CU，Continuous Update)模式和B_nT＞0.1的离散更新(DU，Discrete Update)模式两种情况下的DPLL的设计方法，按照该方法可设计任意阶稳定的DPLL，且归一化因子B_nT的限制也被消除。可控根算法在简化高阶稳定环路设计的同时，提供了一组新的环路设计参数B_n、λ_i、η_i ²。其中，B_n为环路的单边等效噪声带宽，λ_i为相对衰减参数，η_i ²决定了环路的阻尼特性。 Among them, the above-mentioned loop filter parameters are determined by the controllable root algorithm. In order to solve the problems in the method of designing digital loops by analog loops, STEPENS SA and THOMAS J.B. proposed the design of DPLL (DigitalPLL, all-digital phase-locked loop) Controllable root formula, this group of formulas gives the design of DPLL in two cases of B _n T<0.1 continuous update (CU, Continuous Update) mode and B _n T>0.1 discrete update (DU, Discrete Update) mode According to this method, a stable DPLL of any order can be designed, and the limitation of the normalization factor B _n T is also eliminated. While simplifying the design of high-order stable loops, the controllable root algorithm provides a new set of loop design parameters B _n , λ _i , η _i ² . Among them, B _n is the unilateral equivalent noise bandwidth of the loop, λ _i is the relative attenuation parameter, and η _i ² determines the damping characteristics of the loop.

以下为可控根算法的具体过程： The following is the specific process of the controllable root algorithm:

在CU模式下，当更新时间T足够小时，DPLL近似APLL(Analog PLL，模拟锁相环)，假设其系统传输函数为 In CU mode, when the update time T is small enough, DPLL approximates APLL (Analog PLL, analog phase-locked loop), assuming that its system transfer function is

${H h}_{θ θ} ((s the s)) = = \frac{{k k}_{11} {s the s}^{N N - - 11} + + {k k}_{22} {s the s}^{N N - - 22} + + . . . . . . + + {k k}_{N N}}{{s the s}^{N N} + + {k k}_{11} {s the s}^{N N - - 11} + + {k k}_{22} {s the s}^{N N - - 22} + + . . . . . . + + {k k}_{N N}}$

该系统是N阶N型环路，其开环传输函数的极点均在原点。系统的单边等效噪声带宽为 The system is an N-order N-type loop, and the poles of its open-loop transfer function are all at the origin. The unilateral equivalent noise bandwidth of the system is

${B B}_{n no} = = {&Integral; &Integral;}_{00}^{\infty \infty} {| | H h ((j j 22 πf πf)) | |}^{22} df df$

求解方程即可得到CU近似下环路带宽B_n与环路系数k_i的关系表达式。然后，求解系统的特征方程 By solving the equation, the relationship expression between the loop bandwidth B _n and the loop coefficient k _i under the CU approximation can be obtained. Then, solve the characteristic equation of the system

s^N+k₁s^N-1+k₂s^N-2+...+k_N＝0 s ^N +k ₁ s ^N-1 +k ₂ s ^N-2 +...+k _N ＝0

根据上述特征方程，得到环路系数k_i和特征根s_k之间的关系。 According to the above characteristic equation, the relationship between the loop coefficient _ki and the characteristic root s _k is obtained.

为了建立新的环路设计参数，将上式化简为多个二阶系统及一阶系统的级联，对于每个二阶系统求得特征根为s_i＝-β_i(1±η_i)，对于每个一阶系统求得特征根为s_i＝-2β_i，其中η_i为对应二阶子系统的一元二次方程求根公式中的判别式，而衰减率β_i对应于求根公式中的a/2。 In order to establish new loop design parameters, the above formula is simplified into a cascade of multiple second-order systems and first-order systems, and the characteristic root obtained for each second-order system is s _i =-β _i (1±η _i ), for each first-order system, the characteristic root is obtained as s _i =-2β _i , where η _i is the discriminant in the root-finding formula of the quadratic equation corresponding to the second-order subsystem, and the attenuation rate β _i corresponds to the a/2 in the root formula.

$η_{i}^{2} > 0$ 时对应的子系统为过阻尼； $η_{i}^{2} = 0$ 时对应的子系统为临界阻尼； $η_{i}^{2} < 0$ 时对应的子系统为欠阻尼；对于二阶环路，η_i ²与传统阻尼因子间可按 $ζ_{i}^{2} = 1 / (1 - η_{i}^{2})$ 进行转换，而衰减率β_i与传统的环路自然频率ω_n有关，且β_i＝ζω_n。在确定B_n后之后，选定β₁作为参考衰减参数，并定义新的参数λ_i，β_i＝λ_iβ₁，i≥2称为相对衰减参数。 $η_{i}^{2} > 0$ When the corresponding subsystem is overdamped; $η_{i}^{2} = 0$ When , the corresponding subsystem is critically damped; $η_{i}^{2} < 0$ When the corresponding subsystem is underdamped; for the second-order loop, the relationship between η _i ² and the traditional damping factor can be calculated according to $ζ_{i}^{2} = 1 / (1 - η_{i}^{2})$ Conversion is carried out, and the attenuation rate β _i is related to the traditional loop natural frequency ω _n , and β _i =ζω _n . After determining B _n , select β ₁ as the reference attenuation parameter, and define a new parameter λ _i , β _i = λ _i β ₁ , i≥2 is called the relative attenuation parameter.

为了保证系统的稳定性，参数β₁必须是正数，且仅为B_n的函数。这样对于N阶环路的N个独立可选参数为上述定义的B_n、λ_i、η_i ²。由于β₁＞0，为使环路呈现衰减特性必须使λ_i＞0。定义高阶环路参数的计算公式 $k_{i} = α_{i} k_{1}^{i},$ i＝2，3，...N，这种定义方式使得α_i是没有量纲的。 In order to ensure the stability of the system, the parameter _β1 must be a positive number, and it is only a function of B _n . In this way, the N independent optional parameters for the N-order loop are B _n , λ _i , and η _i ² defined above. Since β ₁ >0, λ _i >0 must be made in order to make the loop exhibit attenuation characteristics. Defining calculation formulas for higher-order loop parameters $k_{i} = α_{i} k_{1}^{i},$ i=2, 3, . . . N, this definition makes α _i dimensionless.

求解α_i的表达式并将其带入环路系数k_i与系统参数B_n和α_i之间的关系式，就可以得到环路系数k_i与系统参数b_n、λ_i、η_i ²间的关系。 Solve the expression of α _i and put it into the relationship between the loop coefficient k _i and the system parameters B _n and α _i , then you can get the loop coefficient k _i and the system parameters b _n , λ _i , η _i ² relationship between.

下表列出了标准欠阻尼情况下，基于CU模式的1～4阶APLL环路系数的求解表达式，对应的DPLL环路的系数K_i＝k_iTⁱ。在本发明实施例中，滤波系数可从下表中对应查出。 The following table lists the solution expressions of the 1st to 4th order APLL loop coefficients based on the CU mode under the standard underdamped condition, and the corresponding DPLL loop coefficient K _i =k _i T ⁱ . In the embodiment of the present invention, the filter coefficients can be correspondingly found from the following table.

108：由该相位(或频率)差控制载波NCO生成新的本地载波。 108: The carrier NCO is controlled by the phase (or frequency) difference to generate a new local carrier. the

需要说明的是，上述过程在跟踪过程中不断循环，最终达到相位(或频率)差无限逼近于零，即实现了精确的载波跟踪。 It should be noted that the above-mentioned process is continuously cyclic during the tracking process, and finally the phase (or frequency) difference is infinitely close to zero, that is, precise carrier tracking is realized. the

需要说明的是，码相位跟踪原理与该原理相同。 It should be noted that the principle of code phase tracking is the same as this principle. the

需要说明的是以上步骤106-步骤108是基于可控根技术的3阶FLL(frequency lock loop，频率锁定环)辅助4阶PLL(phase lock loop，相位锁定环)的载波跟踪过程，是数字锁相环的一种。 It should be noted that the above step 106-step 108 is the carrier tracking process of the third-order FLL (frequency lock loop, frequency locked loop) assisted by the fourth-order PLL (phase lock loop, phase locked loop) based on the controllable root technology, which is a digital lock A type of ring. the

需要说明的是，在跟踪过程中，接收机通过传感器时刻判断自身所处的动态环境，然后在两种跟踪环路中进行切换，从而满足对信号的连续跟踪不失锁。 It should be noted that during the tracking process, the receiver judges the dynamic environment it is in at all times through the sensor, and then switches between the two tracking loops, so as to meet the continuous tracking of the signal without losing the lock. the

本发明通过根据载体的动态特性自适应切换的载波跟踪方法，当载体处于高动态环境时，接收机利用本方案提出的可自适应调整带宽的改进了观测方程的sigma点卡尔曼滤波方法进行载波跟踪；而当载体处于非高动态环境时，切换到高效率的基于连续可控根的数字锁相环进行跟踪，减小环路的误差，提高定位结果刷新率，达到在复杂动态环境中，对信号连续跟踪而不失锁的目的。 The present invention adopts the carrier tracking method of adaptively switching according to the dynamic characteristics of the carrier. When the carrier is in a high dynamic environment, the receiver uses the sigma point Kalman filter method of the improved observation equation that can adaptively adjust the bandwidth proposed by the program to perform carrier tracking. Tracking; and when the carrier is in a non-high dynamic environment, switch to a high-efficiency digital phase-locked loop based on continuous controllable root for tracking, reduce the error of the loop, improve the refresh rate of positioning results, and achieve in complex dynamic environments, The purpose of continuously tracking the signal without losing the lock. the

实施例2 Example 2

为了适应复杂的动态环境，使跟踪环路能够根据动态环境的变化切换载波跟踪方法，环路带宽具有一定的自适应调整能力，在高动态环境中具有较宽的带宽，在非高动态环境中具有较小的带宽，并兼顾环路的捕获性能和稳态的跟踪性能，本发明实施例提供了一种卡尔曼滤波装置。参见图2，该装置具体包括： In order to adapt to the complex dynamic environment, so that the tracking loop can switch the carrier tracking method according to the change of the dynamic environment, the loop bandwidth has a certain ability of self-adaptive adjustment, it has a wider bandwidth in the high dynamic environment, and in the non-high dynamic environment The embodiment of the present invention provides a Kalman filter device with a small bandwidth and taking into account both loop capture performance and steady-state tracking performance. Referring to Figure 2, the device specifically includes:

第一处理模块201，用于对接收到的信号进行处理，得到接收信号，并从该接收信号中提取观测值，该接收信号包括接收载波和接收码； The first processing module 201 is used to process the received signal, obtain the received signal, and extract the observed value from the received signal, the received signal includes a received carrier and a received code;

更新模块202，用于对该接收信号的状态值进行更新； Update module 202, for updating the status value of the received signal;

观测模块203，用于用该观测值修正更新后的状态值，得到当前状态的最终估计值；该观测值通过观测方程得到， The observation module 203 is used to correct the updated state value with the observed value to obtain the final estimated value of the current state; the observed value is obtained through the observation equation,

第一生成模块204，用于利用该状态的最终估计值控制NCO产生新的信号。 The first generating module 204 is configured to use the final estimated value of the state to control the NCO to generate a new signal. the

本发明实施例提供了一种利用数字锁相环滤波装置，参见图3，该装置具体包括： An embodiment of the present invention provides a digital phase-locked loop filter device, see Figure 3, the device specifically includes:

第二处理模块301，用于对接收到的信号进行处理，得到接收信号，该接收信号包括接收载波和接收码； The second processing module 301 is used to process the received signal to obtain a received signal, which includes a received carrier and a received code;

差值模块302，用于计算本地信号与该接收信号之间的相位差或频率差； difference module 302, for calculating the phase difference or frequency difference between the local signal and the received signal;

环路滤波模块303，用于利用环路滤波参数对该相位差或频率差进行环路滤波； The loop filter module 303 is used to perform loop filter on the phase difference or frequency difference by using the loop filter parameters;

第二生成模块304，用于利用该相位差或频率差控制NCO生成新的本地信号。 The second generation module 304 is configured to use the phase difference or the frequency difference to control the NCO to generate a new local signal. the

本发明提供了一种信号跟踪的装置，参见图4，该装置具体包括： The present invention provides a device for signal tracking, see Figure 4, the device specifically includes:

处理模块401，用于对接收到的信号进行处理，得到接收信号，并从该接收信号中提取观测值，该接收信号包括接收载波和接收码； The processing module 401 is used to process the received signal, obtain the received signal, and extract the observed value from the received signal, the received signal includes a received carrier and a received code;

判断模块402，用于判断接收机的速度、加速度或加加速度是否大于预设的阈值，如果是，触发用于该载体处于高动态环境，利用卡尔曼滤波进行信号跟踪的卡尔曼滤波模块403；如果否，触发用于该载体处于非高动态环境，利用数字锁相环进行信号跟踪的数字锁相环模块404。 Judging module 402, used to judge whether the speed, acceleration or jerk of the receiver is greater than a preset threshold, if so, trigger the Kalman filter module 403 for the carrier to be in a high dynamic environment and use Kalman filter for signal tracking; If not, trigger the digital phase-locked loop module 404 for signal tracking using a digital phase-locked loop for the carrier in a non-high dynamic environment. the

该卡尔曼滤波模块403中的观测方程为 The observation equation in the Kalman filtering module 403 is

该数字锁相环模块404的环路滤波参数是利用可控根算法得到的。 The loop filter parameters of the digital phase-locked loop module 404 are obtained by using the controllable root algorithm. the

发明通过根据载体的动态特性自适应切换的载波跟踪装置，当载体处于高动态环境时，接收机利用本方案提出的可自适应调整带宽的改进了观测方程的sigma点卡尔曼滤波方法进行载波跟踪；而当载体处于非高动态环境时，切换到高效率的基于连续可控根的数字锁相环进行跟踪，减小环路的误差，提高定位结果刷新率，达到在复杂动态环境中，对信号连续跟踪而不失锁的目的。 The invention uses the carrier tracking device for adaptive switching according to the dynamic characteristics of the carrier. When the carrier is in a high dynamic environment, the receiver uses the sigma point Kalman filter method of the improved observation equation that can adaptively adjust the bandwidth proposed by this program to perform carrier tracking. ; and when the carrier is in a non-high dynamic environment, switch to the high-efficiency digital phase-locked loop based on continuous controllable root for tracking, reduce the error of the loop, improve the refresh rate of positioning results, and achieve the goal of positioning in a complex dynamic environment. The purpose of continuous signal tracking without losing lock. the

实施例3 Example 3

为了适应复杂的动态环境，使跟踪环路能够根据动态环境的变化切换载波跟踪方法，环路带宽具有一定的自适应调整能力，在高动态环境中具有较宽的带宽，在非高动态环境中具有较小的带宽，并兼顾环路的捕获性能和稳态的跟踪性能，本发明实施例提供了一种码跟踪的方法。参见图5，该方法具体包括： In order to adapt to the complex dynamic environment, so that the tracking loop can switch the carrier tracking method according to the change of the dynamic environment, the loop bandwidth has a certain ability of self-adaptive adjustment, it has a wider bandwidth in the high dynamic environment, and in the non-high dynamic environment The embodiment of the present invention provides a code tracking method with a small bandwidth and taking into account both loop capture performance and steady-state tracking performance. Referring to Figure 5, the method specifically includes:

501：接收机接收卫星信号，并对接收到的信号进行处理，得到接收信号，将接收信号乘以本地载波的同相与正交分量，再与本地产生的C/A码相乘，得到观测信号，从观测信号中提取当前的观测值； 501: The receiver receives the satellite signal and processes the received signal to obtain the received signal, multiplies the received signal by the in-phase and quadrature components of the local carrier, and then multiplies it with the locally generated C/A code to obtain the observed signal , to extract the current observation value from the observation signal;

其中，接收信号包括但不限于从信号中提取的接收码； Among them, the received signal includes but not limited to the received code extracted from the signal;

502：判断接收机的速度、加速度或加加速度是否大于预设阈值，如果是，则接收机处于高动态，执行步骤503，如果否，接收机处于非高动态，执行步骤506； 502: Judging whether the speed, acceleration or jerk of the receiver is greater than the preset threshold, if yes, the receiver is in high dynamic state, execute step 503, if not, the receiver is in non-high dynamic state, execute step 506;

503：对接收信号进行初始化和状态值更新； 503: Initialize the received signal and update the state value;

504：用步骤501中得到的观测值修正步骤503中更新后的状态值，得到当前状态的最终估计值； 504: Use the observed value obtained in step 501 to correct the updated state value in step 503 to obtain the final estimated value of the current state;

505：利用当前状态的最终估计值控制码NCO产生新的码，结束。 505: Use the final estimated value control code NCO of the current state to generate a new code, and end. the

506：接收信号首先进入到鉴相器，计算出本地码与接收码之间的相位差； 506: The received signal first enters the phase detector to calculate the phase difference between the local code and the received code;

507：利用环路滤波参数对该相位差进行环路滤波； 507: Perform loop filtering on the phase difference by using loop filtering parameters;

其中，该环路滤波参数是利用可控根算法得到的。 Wherein, the loop filter parameters are obtained by using a controllable root algorithm. the

508：利用该相位差控制码NCO生成新的本地码。 508: Generate a new local code by using the phase difference control code NCO. the

该码跟踪的方法的原理与实施例1中提供的载波跟踪的方法的原理相同，具体步骤不再赘述。 The principle of the code tracking method is the same as that of the carrier tracking method provided in Embodiment 1, and the specific steps are not repeated here. the

本发明通过根据载体的动态特性自适应切换的码跟踪方法，当载体处于高动态环境时，接收机利用本方案提出的可自适应调整带宽的改进了观测方程的sigma点卡尔曼滤波方法进行码跟踪；而当载体处于非高动态环境时，切换到高效率的基于连续可控根的数字锁相环进行跟踪，减小环路的误差，提高定位结果刷新率，达到在复杂动态环境中，对信号连续跟踪而不失锁的目的。 The present invention adopts the code tracking method of adaptively switching according to the dynamic characteristics of the carrier. When the carrier is in a high dynamic environment, the receiver uses the sigma point Kalman filter method of the improved observation equation that can adaptively adjust the bandwidth proposed by the program to perform code tracking. Tracking; and when the carrier is in a non-high dynamic environment, switch to a high-efficiency digital phase-locked loop based on continuous controllable root for tracking, reduce the error of the loop, improve the refresh rate of positioning results, and achieve in complex dynamic environments, The purpose of continuously tracking the signal without losing the lock. the

本发明实施例可以利用软件实现，相应的软件程序可以存储在可读取的存储介质中，例如，计算机的硬盘、缓存或光盘中。 The embodiment of the present invention can be realized by software, and the corresponding software program can be stored in a readable storage medium, for example, a hard disk, cache or optical disk of a computer. the

以上所述仅为本发明的较佳实施例，并不用以限制本发明，凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。 The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection of the present invention. within range. the

Claims

1. A method of signal tracking, comprising:

processing a received signal to obtain a received signal, and extracting an observation value from the received signal, wherein the received signal comprises a received carrier and a received code;

judging whether the speed, the acceleration or the jerk of the receiver is larger than a preset threshold value, if not, the carrier is in a non-high dynamic environment, and tracking signals by using a digital phase-locked loop;

if the speed, the acceleration or the jerk of the receiver is not larger than a preset threshold value, the carrier is in a high dynamic environment, and signal tracking is carried out by using Kalman filtering;

the signal tracking by using Kalman filtering comprises:

updating the state value of the received signal;

correcting the updated state value by using the observed value to obtain a final estimated value of the current state; the observed value is obtained by an observation equation,

the observation equation is shown in the following formula,

x (k) is the state value at time k, r_I(k) Is an in-phase component, r_Q(k) Is the quadrature component, A is the amplitude of the received signal, d (k) takes the value ± 1, θ (k) = L^TX(k)，L=[1，0，0，0]^TN' (k) is an observation noise vector;

the final estimate of the state is used to control the NCO to generate a new signal.

2. The method of claim 1, wherein the loop filter parameters of the digital phase locked loop are obtained using a controllable root algorithm.

3. An apparatus for signal tracking, comprising:

the device comprises a first processing module, a second processing module and a control module, wherein the first processing module is used for processing a received signal to obtain a received signal and extracting an observation value from the received signal, and the received signal comprises a received carrier and a received code;

the device comprises a judging module, a digital phase-locked loop module, a Kalman filtering module and a signal tracking module, wherein the judging module is used for judging whether the speed, the acceleration or the jerk of a receiver is greater than a preset threshold value or not, if not, the digital phase-locked loop module is used for triggering a carrier to be in a non-high dynamic environment and performing signal tracking by using a digital phase-locked loop, and if the speed, the acceleration or the jerk of the receiver is not greater than the preset threshold value, the Kalman filtering module is used for triggering the carrier to be in a high;

the Kalman filtering module comprises:

the updating module is used for updating the state value of the received signal;

the observation module is used for correcting the updated state value by using the observation value to obtain a final estimation value of the current state; the observed value is obtained by an observation equation,

the observation equation is shown in the following formula,

x (k) is the state value at time k, r_I(k) Is an in-phase component, r_Q(k) Is the quadrature component, a is the amplitude of the received signal, d (k) takes the value ± 1, θ (k) is L^TX(k)，L＝[1，0，0，0]^TN' (k) is an observation noise vector;

and the first generation module is used for controlling the NCO to generate a new signal by utilizing the final estimated value of the state.

4. The apparatus of claim 3, wherein the loop filter parameters of the digital phase-locked loop module are obtained using a controllable root algorithm.