CN102638319B - Modulation performance test method for navigational satellite binary offset carrier signal - Google Patents

Abstract

The invention discloses a modulation performance test method for a navigational satellite binary offset carrier signal. The modulation performance test method comprises the following steps of: firstly, carrying out direct A/D sampling on a BOC (binary offset carrier) modulation navigation signal of a navigational satellite downlink transmission microwave frequency band; then, carrying out variable-frequency filtering and hilbert transform on the signal in a numeric field; carrying out quadrature demodulation, channel gain compensation and phase compensation processing in digital communication, and filtering by a measurement filter to obtain measured data; carrying out symbol detection, reference signal generation processing and reference filtering on the measured data to obtain reference data; and calculating the reference data and the measured data to obtain a parameter and a signal graph which reflects the base band modulation performance. The BOC carrier modulation signal is processed in the numeric field by the modulation performance test method. Because a BOC single sideband frequency spectrum is extracted in the numeric field, the problem that the BOC signal can not be subjected to the modulation characteristic test through a vector signal analysis method because of subcarrier can be solved.

Description

A Modulation Performance Test Method of Navigation Satellite Binary Offset Carrier Signal

technical field

The invention relates to a method for testing the modulation performance of navigation satellite downlink broadcasting signals.

Background technique

At present, my country is developing a new generation of global navigation satellite systems. The difference from the previous generation of regional satellite navigation systems is that in order to improve the accuracy and anti-interference ability of satellite navigation signals, BOC (binary offset) will be added to the signal system of navigation satellites. The baseband modulation performance of the navigation signal is an important aspect of the navigation signal performance. In the satellite development process, the baseband modulation performance parameter of the downlink navigation performance of the navigation satellite is the key parameter in the whole satellite test.

The baseband modulation performance test of the existing digital modulation signal generally adopts the following two methods: (1) using a vector signal analyzer, such as the FSQ sequence of the German R/S company and the 89600 series and E4406VSA series vector signal analyzers of the American Agilent. (2) Use an oscilloscope or a spectrum analyzer in combination with vector signal analysis software, such as Agilent's 89600s vector signal analysis software. Existing commercialized vector signal analyzers or vector signal analysis software are only applicable to traditional digital modulation signals, such as PSK, GMSK, MSK and other modulation signals. Since BOC is a new type of digital modulation signal, it is mainly used for navigation signals. The parameters of the modulation signal are not only related to the carrier frequency and code rate, but also related to the subcarrier frequency. However, the existing commercial analyzers or vector signal analysis software only For the carrier frequency and code rate, it is impossible to complete the test of all baseband modulation performance parameters of the BOC modulated navigation signal.

There are also many literatures on vector signal analysis, but the methods described in these literatures have the following two types of deficiencies: the first type is that the training sequence signal is required to perform channel estimation on the process of signal frequency conversion processing, in order to complete the channel amplitude compensation and The parameter setting of the phase compensation algorithm requires the generation of high-quality training signals. Such as the method given in the document "Key Algorithms for Accurate GSM EDGE EVMMasurement on ATE Platform" (Shu Xia, 8th International Conference on Solid-State and Integrated Circuit Technology, 2006.ICSICT'06.). For high-quality navigation satellite BOC signals, it means that a higher-quality BOC signal source is needed to calibrate the test system, which is very difficult in actual work. The second category requires the use of adaptive equalization techniques for channel estimation of the receiving channel, such as the method given in the document "EVM measurement techniques for MUOS" (McAllister, IEEE Military Communications Conference, 2009.MILCOM 2009.). Because the modulation quality of the navigation signal is high, the estimated error will affect the test result, and the channel estimation algorithm is complicated to realize in this method.

Contents of the invention

The technical solution of the present invention is to overcome the deficiencies of the prior art and provide a method for testing the modulation performance of navigation satellite BOC signals, which can realize the testing of the baseband modulation performance parameters of BOC modulated navigation signals.

The technical solution of the present invention is: a kind of modulation performance testing method of navigation satellite binary offset carrier signal, the steps are as follows:

(1) Carry out direct analog-to-digital sampling to the binary offset carrier modulation signal broadcast by the navigation satellite downlink;

(2) Carry out digital mixing and digital low-pass filtering to the direct analog-to-digital sampling data to obtain the intermediate frequency binary offset carrier digital signal;

(3) uniformly extract the intermediate frequency binary offset carrier digital signal;

(4) Carry out digital low-pass filtering again to the binary offset carrier digital signal after uniform extraction, extract the lower sideband in the two signal spectrums contained in the binary offset carrier digital signal in the frequency domain, and suppress the upper sideband spectrum ;

(5) Perform Hilbert transform on the output signal after digital low-pass filtering again to obtain complex data, then use the Costas loop to perform carrier tracking on the complex data, and perform channel gain compensation and phase on the output signal after carrier tracking Compensate to get the baseband signal;

(6) Determine the transfer function of the matching test filter according to the characteristics of the shaping filter at the transmitter of the binary offset carrier signal of the navigation satellite, and then use the test filter to filter the baseband signal after channel gain compensation and phase compensation to obtain IQ baseband waveform data to be measured;

(7) According to the PSK modulation method, carry out symbol bit detection on the IQ baseband waveform data to be measured to obtain the symbol bit data, and then generate the IQ ideal baseband according to the symbol bit synchronization error information obtained by the PSK baseband modulation method, symbol bit rate and timing recovery processing Signal;

(8) reference filter is set according to the characteristics of navigation satellite binary offset carrier signal transmission channel shaping filter and test filter, then utilize reference filter to filter IQ ideal baseband signal, form IQ baseband reference waveform data;

(9) Calculate the error value between the IQ baseband waveform data to be measured and the IQ baseband reference waveform data, perform vector error processing on the error value, and obtain parameters and signal diagrams reflecting the baseband modulation performance.

In the step (1), the sampling rate of A/D sampling is greater than 10 times of the pseudo-random code rate of the binary offset carrier modulation navigation signal, and the number of chips adopted is greater than 200.

The advantage of the present invention compared with prior art is:

(1) The inventive method does not carry out the frequency conversion process to the BOC signal broadcast by the navigation satellite, but processes it in the digital domain after direct A/D sampling, avoiding the amplitude phase distortion that the frequency conversion process brings to the BOC signal modulation performance test result Impact;

(2) In the process of digital domain processing, one of the BOC double sideband spectrum is extracted, and the vector signal analysis method of traditional digital PSK modulation is used to analyze the BOC modulation characteristic parameters, which solves the problem that the BOC signal cannot be used due to the existence of subcarriers. The problem of baseband modulation characteristic testing by vector signal analysis method;

(3) The carrier rotator is used in the digital COSTAS loop to eliminate the low-pass filter of the IQ branch during carrier synchronization, avoiding the compensation of the low-pass filter of the IQ branch during gain and phase compensation, and reducing the difficulty of processing ;

(4) In the usual vector signal method of IF sampling for modulation performance testing, a training sequence signal is required for channel estimation or adaptive blind channel estimation to realize gain compensation and phase compensation, which is complicated to implement, and the measurement system adapts to the energy difference. In the method of this aspect, the BOC carrier modulation signal is directly sampled, and the signal frequency conversion and filtering processing are all carried out in the digital domain. When performing gain compensation and phase compensation, the equalization algorithm of the channel is simple to implement, and the equalization effect is good. The BOC signal modulation performance analysis process The amplitude and phase distortion in the channel are perfectly compensated, and the influence of the amplitude and phase characteristics of the channel on the test results can be ignored.

Description of drawings

Fig. 1 is a block diagram of the inventive method;

Fig. 2 is the frequency spectrum of Galileo navigation satellite E1A signal BOC (15, 2.5) navigation signal;

Fig. 3 is the magnitude-frequency-phase-frequency characteristic of the low-pass filter after the digital frequency mixing;

Fig. 4 is the tap coefficient of the low-pass filter after digital frequency mixing;

Fig. 5 is the frequency spectrum of the intermediate frequency BOC signal output by the low-pass filter after the digital frequency mixing;

Fig. 6 is the amplitude-frequency-phase-frequency characteristic of the low-pass filter after extraction;

Fig. 7 is the tap coefficient of the low-pass filter after extraction;

FIG. 8 is the frequency spectrum of the intermediate frequency BOC signal output by the low-pass filter after extraction.

Detailed ways

As shown in Figure 1, it is a schematic diagram of the method of the present invention. The method of the invention mainly includes direct A/D sampling and digital domain signal processing of BOC navigation signals broadcast by navigation satellites. Use A/D sampling to directly sample the BOC navigation signal in the microwave frequency band broadcast by the navigation satellite. The sampled data is down-converted and low-pass filtered, and then extracted and band-pass filtered to extract the two signal spectra in the BOC signal spectrum structure. One performs quadrature demodulation. Perform channel gain and phase compensation according to the characteristics of the receiving channel, and then perform measurement filter filtering according to the characteristics of the navigation satellite BOC signal transmission channel to generate IQ baseband test signal waveforms, and generate IQ baseband reference signal waveforms according to the modulation method, symbol rate and characteristics of the transceiver channel Data, IQ baseband reference signal waveform data and IQ baseband test signal waveform data to calculate the error, and then process to obtain the measurement results of BOC modulation performance parameters.

The method of the present invention will be described in detail below by taking the Galileo navigation satellite E1A signal as an example. The BOC modulation method is represented by BOC(α, β), where the parameter β represents the code rate normalized with 1.023Mcps as the base, and the parameter α represents the subcarrier frequency normalized with 1.023Mcps as the base. The central frequency of the E1A signal is 1575.42MHz, the modulating signal form is BOC(15, 2.5), which means the rate of the pseudo-random code is 2.5×1.023=2.5625Mcps, and the subcarrier frequency is 15×1.023=15.345MHz. (1) First, use an analog spread spectrum signal source to generate an analog Galileo navigation satellite E1A signal, the center frequency is 1575.42MHz, the modulation signal form is BOC (15, 2.5), and the A/D sampler with a sampling rate of 5GHz is used for E1A The navigation signal is directly sampled at high speed. Here, the sampling time is 0.5ms, the number of chips used is 1281, and the number of sampling points is 2500000. The spectrum of the BOC signal is shown in Figure 2.

(2) Generate a local 1545.42MHz digital local oscillator signal in the digital domain, and perform digital frequency mixing and digital low-pass filtering on the sampling data. Low-pass filter 1 selects FIR filter, and the mathematical expression of its transfer function is:

${\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

f_s为采样频率，这里为5Gsa/s。In the formula, C _i is the i-th tap coefficient of the low-pass filter 1, M ₁ is the order of the low-pass filter 1,

f _s is the sampling frequency, here it is 5Gsa/s.

In this example, the order of low-pass filter 1 is 156, its amplitude-frequency and phase-frequency characteristics are shown in Figure 3, and the coefficients of each tap are shown in Figure 4. After low-pass filtering, the BOC digital signal with a center frequency of 30 MHz is obtained, and the frequency spectrum of the intermediate frequency BOC signal output by the low-pass filter 1 is as shown in Figure 5;

(3) Select an extraction coefficient of 10, uniformly extract the intermediate frequency BOC digital signal, and perform digital low-pass filtering on the extracted BOC signal data again. The low-pass filter 2 is also an FIR filter, and the mathematical expression of its transfer function is: :

${\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

M为抽取率系数。In the formula, F _i is the i-th tap coefficient of the low-pass filter 2, M ₂ is the order number of the low-pass filter 2,

M is the sampling rate coefficient.

In this example, the second order of the low-pass filter is 78, its amplitude-frequency and phase-frequency characteristics are shown in Figure 6, and the tap coefficients are shown in Figure 7. Low-pass filter 2 extracts the lower sideband signal spectrum in the two sidebands in the BOC signal spectrum, suppresses the upper sideband spectrum, and the signal spectrum of low-pass filter 2 output is as shown in Figure 8;

(4) For the single signal output by the low-pass filter 2, first perform Hilbert transform, convert it into complex data, and then use the Costas composed of a phase detector, a loop filter, a carrier rotator and a digital voltage-controlled oscillator. The loop performs carrier tracking of the input complex data. The single signal spectrum structure output signal s(k) of the low-pass filter 2 output is expressed as:

$\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; a</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}\frac{\mathrm{<span\; class="notranslate">\; m</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; cos</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&pi;f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}\mathrm{<span\; class="notranslate">\; k</span>}\frac{\mathrm{<span\; class="notranslate">\; m</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

为低通滤波器2输出信号第k个样本点的幅度，f_i为低通滤波器2输出信号的中心载波频率，θ_i为低通滤波器2输出信号第k个样本点初始相位。In the formula

is the amplitude of the kth sample point of the output signal of low-pass filter 2, f _i is the center carrier frequency of the output signal of low-pass filter 2, and _θi is the initial phase of the k-th sample point of the output signal of low-pass filter 2.

The complex number S(k) formed after Hilbert transform is expressed as:

$\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; A</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}\frac{\mathrm{<span\; class="notranslate">\; m</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; e</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&pi;f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}\mathrm{<span\; class="notranslate">\; k</span>}\frac{\mathrm{<span\; class="notranslate">\; m</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; )</span>$

为信号s(k)的幅度。In the formula

is the magnitude of the signal s(k).

In this way, the signal I(k) of the I branch is expressed as:

$\mathrm{<span\; class="notranslate">\; I</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; A</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}\frac{\mathrm{<span\; class="notranslate">\; m</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; cos</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&pi;f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}\mathrm{<span\; class="notranslate">\; k</span>}\frac{\mathrm{<span\; class="notranslate">\; m</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 5</span>}<span\; class="notranslate">\; )</span>$

The signal Q(k) of the Q branch is expressed as:

$\mathrm{<span\; class="notranslate">\; Q</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; A</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}\frac{\mathrm{<span\; class="notranslate">\; m</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; sin</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&pi;f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; +</span>\frac{\mathrm{<span\; class="notranslate">\; m</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 6</span>}<span\; class="notranslate">\; )</span>$

The transfer function _HR (k) of the carrier rotator is:

${\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; R</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&pi;</span>}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}\mathrm{<span\; class="notranslate">\; k</span>}\frac{\mathrm{<span\; class="notranslate">\; m</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 7</span>}<span\; class="notranslate">\; )</span>$

Where f ₀ is the frequency generated by the digital voltage-controlled oscillator.

The output signal S _P (k) after passing through the carrier rotator is:

S _P (k) = S (k) H _R (k) (8)

The IQ branch signals I _P (k) and Q _P (k) of the output signal S _P (k) after the carrier rotator are respectively:

${\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; P</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; A</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}\frac{\mathrm{<span\; class="notranslate">\; m</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; cos</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&pi;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; k</span>}\frac{\mathrm{<span\; class="notranslate">\; m</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 9</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; P</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; A</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}\frac{\mathrm{<span\; class="notranslate">\; m</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; sin</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&pi;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; k</span>}\frac{\mathrm{<span\; class="notranslate">\; m</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 10</span>}<span\; class="notranslate">\; )</span>$

Perform phase detection on the output signal of the carrier rotator, such as using the phase detection method of the arctangent function to calculate the phase difference φ _e (k) of each sample point:

${\mathrm{<span\; class="notranslate">\; \&phi;</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; arctan</span>}<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; P</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span>}{{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; P</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 11</span>}<span\; class="notranslate">\; )</span>$

(5) According to the transfer function of the low-pass filter 1 after digital mixing and the low-pass filter 2 after extraction, calculate the transfer function _HR of the entire receiving channel:

${\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; R</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&CircleTimes;</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 12</span>}<span\; class="notranslate">\; )</span>$

表示循环卷积。然后，计算通道增益补偿和相位补偿处理的传输函数H_C，In the formula

Represents circular convolution. Then, calculate the transfer function H _C of the channel gain compensation and phase compensation processing,

${\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; C</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; R</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 13</span>}<span\; class="notranslate">\; )</span>$

(6) Perform channel gain compensation and phase compensation processing on the output signal set S _P after the carrier tracking of the Costas loop, and the output signal set S _P is composed of each S _P (k).

(7) BOC modulation signals of navigation satellites are often shaped and filtered at the transmitting end to limit the transmission bandwidth and reduce intersymbol interference, while reducing signal loss as much as possible. Therefore, in order to eliminate the influence of the transmitting channel on the analysis results of the modulated signal, a measurement filter is generated according to the characteristics of the navigation satellite BOC modulated signal generation and the transmitting channel, and the measurement filter matches the shaping filter of the navigation satellite BOC signal transmitting end. There are many forms of shaping filters, such as raised cosine filter, root raised cosine filter, Gaussian filter, etc. Different filters have different time-frequency responses, so it must be correctly selected according to the characteristics of the shaping filter at the transmitter of the navigation satellite BOC signal. Here, it is assumed that in order to make the transfer function of the entire navigation satellite BOC signal transmission and reception system have a raised cosine characteristic without intersymbol interference, and considering the transmission and reception matching requirements of the largest signal-to-noise ratio at the sampling time, the frequency domain of the shaping filter at the transmitting end The characteristic is an approximate root-raised cosine characteristic, so the measurement filter selects the root-raised cosine filter. According to the roll-off coefficient α (0 ≤ α ≤ 1) and the symbol bit rate of the root raised cosine filter, the order and tap coefficient of the root raised cosine filter are calculated and determined by Matlab software, where the symbol bit rate is twice the subcarrier frequency , namely 30.69MHz, the mathematical expression of the root raised cosine filter transfer function H _st is:

${\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; st</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 14</span>}<span\; class="notranslate">\; )</span>$

In the formula, N is the order of the root raised cosine filter, and R _i is the i-th tap coefficient of the root raised cosine filter.

After shaping and filtering, the waveform data set S _T required for IQ baseband measurement is obtained:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; P</span>}}<span\; class="notranslate">\; \&CircleTimes;</span><span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; \&CircleTimes;</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; st</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ]</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 15</span>}<span\; class="notranslate">\; )</span>$

(8) According to the PSK modulation mode, carry out sign bit detection to IQ baseband wave data to be measured, obtain sign bit data, then generate IQ ideal baseband signal according to PSK baseband modulation mode, sign bit rate and sign bit synchronization error information; sign bit synchronization The error information is realized by coincident timing recovery, and the realization of coincident timing recovery can use methods commonly used in digital communication systems: Miller-Muller algorithm, Gardner algorithm and early-late gate algorithm.

(9) According to the characteristics of the BOC signal transmission channel shaping filter and the measurement filter, the reference filter parameters are set; the reference filter is used to balance the joint influence of the BOC signal transmission channel shaping filter and the measurement filter, here, the BOC signal transmission channel Both the shaping filter and the measurement filter are root-raised cosine filters, and their transfer functions are both H _st , so the mathematical expression H _sr of the reference filter transfer function can be determined as:

${\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; sr</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; st</span>}}<span\; class="notranslate">\; \&CircleTimes;</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; st</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 16</span>}<span\; class="notranslate">\; )</span>$

After the signal is processed by the reference filter, the IQ baseband reference signal waveform data set S _R is formed:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; R</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; \&CircleTimes;</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; sr</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 17</span>}<span\; class="notranslate">\; )</span>$

(9) Calculate the error value between the IQ baseband measurement signal waveform data and the IQ baseband reference signal waveform data, and carry out vector error processing on the error value, thereby obtaining parameters and signal diagrams reflecting the baseband modulation performance, including: vector magnitude error EVM , vector phase error EVP, spectrum diagram of error vector, time domain waveform of error vector, etc.

Vector error EV calculation:

EV (k) = S _T (k) - S _R (k) (18)

In the formula, _ST (k) is the kth data in the waveform data set _ST required for IQ baseband measurement, and S _R (k) is the kth data in the IQ baseband reference signal waveform data set S _R .

Vector magnitude error EVM calculation:

${\mathrm{<span\; class="notranslate">\; EVM</span>}}_{\mathrm{<span\; class="notranslate">\; RMS</span>}}<span\; class="notranslate">\; =</span>\sqrt{\frac{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; +</span>}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; EV</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 19</span>}<span\; class="notranslate">\; )</span>$

In the formula, N is the total number of data involved in the calculation.

Vector phase error EVP calculation:

$\mathrm{<span\; class="notranslate">\; EVP</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; arctan</span>}<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; Re</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; EV</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; Im</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; EV</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 20</span>}<span\; class="notranslate">\; )</span>$

In the formula, Re(EV(k)) represents the real part of EV(k), and Im(EV(k)) represents the imaginary part of EV(k);

The frequency spectrum of the error vector can be obtained by performing FFT processing on the vector error EV.

The content that is not described in detail in the description of the present invention belongs to the well-known technology of those skilled in the art.

Claims (2)

1. a modulating performance method of testing for navigation satellite binary offset carrier (AltBOC) signal, is characterized in that step is as follows:

(1) the descending binary offset carrier (boc) modulated signals of broadcasting of navigation satellite is carried out to direct modulus sampling;

(2) direct modulus sampled data is carried out to digital mixing, digital low-pass filtering, obtain intermediate frequency binary offset carrier digital signal;

(3) intermediate frequency binary offset carrier digital signal is evenly extracted;

(4) the intermediate frequency binary offset carrier digital signal after step (3) evenly extracts is carried out to digital low-pass filtering again, in frequency domain, extract the lower sideband in two signal spectrums that the binary offset carrier digital signal after digital low-pass filtering comprises, and upper sideband spectrum is suppressed;

(5) output signal after digital low-pass filtering is again carried out to Hilbert transform and obtain complex data, then utilize Costas loop to carry out carrier track to complex data, and the output signal completing after carrier track is carried out to channel gain compensation and phase compensation, obtain baseband signal;

(6) according to the transfer function of the definite test filter matching of the characteristic of navigation satellite binary offset carrier (AltBOC) signal transmitting terminal formed filter, then utilize test filter to carry out filtering to the baseband signal after channel gain compensation and phase compensation, obtain IQ base band Wave data to be measured;

(7) according to PSK modulation system, IQ base band Wave data to be measured is carried out to sign bit detection, obtain sign bit data, the sign bit synchronous error Information generation IQ ideal baseband signal then obtaining according to PSK baseband modulation mode, sign bit rate and timing Recovery processing;

(8) according to the characteristic of navigation satellite binary offset carrier (AltBOC) signal transmission channel formed filter and test filter, reference filter is set, then utilizes reference filter to carry out filtering to IQ ideal baseband signal, form IQ base band reference waveform data;

(9) ask for the error amount between IQ base band Wave data to be measured and IQ base band reference waveform data, error amount is carried out to vector error processing, obtain reflecting parameter and the signal graph of baseband modulation performance.

2. the modulating performance method of testing of a kind of navigation satellite binary offset carrier (AltBOC) signal according to claim 1, it is characterized in that: in described step (1), the sample rate of modulus sampling is greater than the more than 10 times of pseudorandom code check of binary offset carrier modulation navigation signal, and the chip number of employing is greater than 200.

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