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CN112904326A - Satellite-borne passive positioning method based on virtual aperture - Google Patents

Satellite-borne passive positioning method based on virtual aperture Download PDF

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CN112904326A
CN112904326A CN202110128572.8A CN202110128572A CN112904326A CN 112904326 A CN112904326 A CN 112904326A CN 202110128572 A CN202110128572 A CN 202110128572A CN 112904326 A CN112904326 A CN 112904326A
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doppler
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azimuth
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CN112904326B (en
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张童
李佳明
杨强
张鑫
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Harbin Institute of Technology Shenzhen
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
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Abstract

一种基于虚拟孔径的星载无源定位方法，涉及一种无源定位方法。对采集到的信号进行慢时间域的多普勒处理，得到时间‑多普勒数据；对信号做短时傅里叶变换，进行时频估计，得到多普勒中心频率和多普勒调频率；通过得到的多普勒中心频率和多普勒调频率对低轨等效斜视距离模型参数进行反演，得到卫星等效速度和等效斜视角；将信号按距离进行多次方位向匹配滤波，得到方位向定位信息；将不同距离处的定位结果按距离重新排列，通过聚焦获得距离向的定位信息；根据距离定位结果，选取更小的距离区间段，进行更精确的距离向定位，从而得到目标的二维定位信息。具有系统架构简单，定位精度高的特点。

Figure 202110128572

A spaceborne passive positioning method based on virtual aperture relates to a passive positioning method. Perform Doppler processing in the slow time domain on the collected signal to obtain time-Doppler data; perform short-time Fourier transform on the signal, and perform time-frequency estimation to obtain the Doppler center frequency and Doppler modulation frequency ; Invert the parameters of the low-orbit equivalent strabismus distance model through the obtained Doppler center frequency and Doppler modulation frequency to obtain the satellite equivalent velocity and equivalent strabismus angle; perform multiple azimuth matching filtering on the signal according to the distance , obtain the azimuth positioning information; rearrange the positioning results at different distances by distance, and obtain the distance positioning information by focusing; according to the distance positioning results, select a smaller distance interval for more accurate distance positioning, thereby Obtain the two-dimensional positioning information of the target. It has the characteristics of simple system architecture and high positioning accuracy.

Figure 202110128572

Description

Satellite-borne passive positioning method based on virtual aperture
Technical Field
The invention relates to a passive positioning method, in particular to a satellite-borne passive positioning method based on a virtual aperture, and belongs to the technical field of satellite-borne passive positioning.
Background
With the development of electromagnetic interference and anti-radiation weapon technology, the concealment of the electronic reconnaissance system is required to be higher, and the active detection and positioning system is being challenged seriously. Passive positioning differs from conventional active positioning systems in that it does not need to emit electromagnetic waves by itself, but rather relies on receiving signal energy emitted by the radiation source to position the radiation source. Due to the passive characteristic of the positioning method, the passive radar has the advantages of low power consumption, long action distance, good concealment, strong anti-interference capability and the like, so that the passive radar has a more important strategic position in modern combat. The common carrying platform of the passive positioning system comprises: airborne platform, carrier-borne platform, satellite-borne platform. The satellite-borne platform is located in the space, so that the satellite-borne passive positioning system has the excellent characteristics of wide detection range, high sensitivity, good maneuverability and no limitation by factors such as weather, national regions and the like, and along with the development of the aerospace technology, the satellite-borne passive positioning system is also paid more attention and is developed.
The satellite-borne passive positioning system comprises a single-satellite passive positioning system and a multi-satellite passive positioning system. Common positioning methods for multi-satellite passive positioning systems include time difference of arrival positioning, frequency difference of arrival positioning, and a combination of the two. Although the multi-satellite system has high positioning accuracy, the system is complex to implement and high in cost, and the problems of time synchronization and the like need to be considered, so that the practical application situation is complex. In contrast, although the volume and the load of a single satellite are limited by the erection of an antenna, which results in poor positioning accuracy of a single-satellite passive positioning system, the cost is low, the system is simple to erect, and the actual application situation is simple, so that the system is widely applied.
The single-satellite passive positioning method has many, the most common method is a two-dimensional phase interferometer direction-finding positioning method, the basic principle of the method is that a direction line pointing to a radiation source is obtained by using a phase method for direction finding, and the intersection point of the direction line and the ground is the position of the radiation source. The method can realize instantaneous positioning of the target, and the positioning precision is ideal. However, the positioning accuracy of the method depends on the length of the base line to a certain extent, the measurement accuracy becomes better along with the increase of the length of the base line, and the problem of phase ambiguity is caused by the overlong length of the base line. To solve the phase ambiguity problem, a more complicated antenna structure needs to be constructed or multiplexing needs to be performed. In practical engineering, the following two methods are generally adopted to solve the phase ambiguity problem: one method is to adopt a method of multi-baseline phase comparison angle measurement, form two long baselines and two short baselines in the same direction, the long baseline improves the precision, the short baseline solves the ambiguity, but in the actual system needs a plurality of antennas, because the satellite limits the antenna array shape and the array element number, the effect of solving the phase ambiguity by the method is limited. Another method for solving the phase ambiguity is to increase the number of receiving channels, one path of which can measure the angle without ambiguity by using the amplitude method although the angle measurement accuracy is low, and the other path of which can improve the angle measurement accuracy by using the direction measurement method, which obviously increases the complexity and cost of the device. Therefore, for a single-satellite passive positioning system, it is a worthy direction to reduce the complexity of the system as much as possible while ensuring the positioning accuracy.
Disclosure of Invention
In order to solve the contradiction between the positioning accuracy and the system complexity of the traditional single-satellite passive positioning system, the invention provides a satellite-borne passive positioning method based on a virtual aperture.
In order to achieve the purpose, the invention adopts the following technical scheme: a satellite-borne passive positioning method based on a virtual aperture comprises the following steps:
the method comprises the following steps: performing Doppler processing of a slow time domain on the acquired signals to obtain time-Doppler data;
step two: performing short-time Fourier transform on the signal, and performing time-frequency estimation to obtain Doppler center frequency and Doppler modulation frequency;
step three: inverting the low-orbit equivalent squint distance model parameters through the obtained Doppler center frequency and the obtained Doppler frequency to obtain the satellite equivalent speed and the equivalent squint angle;
step four: carrying out azimuth matching filtering on the signals for multiple times according to the distance to obtain azimuth positioning information;
step five: rearranging the positioning results at different distances according to the distance, and obtaining positioning information in the distance direction through focusing;
step six: and selecting a smaller distance interval according to the distance positioning result, repeating the fourth step and the fifth step, and performing more accurate distance positioning to obtain the two-dimensional positioning information of the target.
Compared with the prior art, the invention has the beneficial effects that: the invention relates to a passive positioning algorithm for positioning a radiation source by using a virtual aperture under a satellite-borne condition, which aims to solve the contradiction between the complexity and the positioning precision of the traditional single-satellite passive positioning system.
Drawings
FIG. 1 is a schematic diagram of an embodiment of the present invention;
FIG. 2 is a diagram illustrating the result of step one in an embodiment of the present invention;
FIG. 3 is a diagram illustrating the result of step five in the example of the present invention.
Detailed Description
The technical solutions in the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the invention, rather than all embodiments, and all other embodiments obtained by those skilled in the art without any creative work based on the embodiments of the present invention belong to the protection scope of the present invention.
A satellite-borne passive positioning method based on a virtual aperture comprises the following steps:
the method comprises the following steps: performing Doppler processing of a slow time domain on the acquired signals to obtain time-Doppler data;
step two: performing short-time Fourier transform on the signal, and performing time-frequency estimation to obtain Doppler center frequency and Doppler modulation frequency;
step three: inverting the low-orbit equivalent squint distance model parameters through the obtained Doppler center frequency and the obtained Doppler frequency to obtain the satellite equivalent speed and the equivalent squint angle;
step four: carrying out azimuth matching filtering on the signals for multiple times according to the distance to obtain azimuth positioning information;
step five: rearranging the positioning results at different distances according to the distance, and obtaining positioning information in the distance direction through focusing;
step six: and selecting a smaller distance interval according to the distance positioning result, repeating the fourth step and the fifth step, and performing more accurate distance positioning to obtain the two-dimensional positioning information of the target.
Preferably, the method for obtaining the time-doppler data in the step one comprises:
the dimension of the fast time domain of the acquired signals is R, Fourier transform is carried out along the slow time axis, and the dimension of the Doppler domain of the data is D, so that the obtained time-Doppler two-dimensional data is { data }, the dimension is R multiplied by D, the repetition frequency of signal pulses is PRF, and the synthetic aperture time is D/PRF.
Preferably, the method for obtaining the doppler center frequency and the doppler modulation frequency in the step two comprises:
doppler parameter estimation is carried out, in order to ensure the accuracy of parameter estimation, short-time Fourier transform of the azimuth direction is carried out on the acquired signals, time-frequency estimation is carried out, the window length of the short-time Fourier transform is L, the step length is M, and the number of data segments is
Figure BDA0002924787910000041
Performing linear fitting on each section of data center to obtain Doppler center frequency fdcAnd Doppler frequency f1r。
Preferably, the method for obtaining the satellite equivalent velocity and the equivalent squint angle in the third step is as follows:
for the satellite-borne situation, an equivalent strabismus distance model is selected, and the model expression is as follows:
Figure BDA0002924787910000051
wherein R iscIs the distance, V, of the target at the time of the beam centerrIs the equivalent velocity of the satellite, θrIs the equivalent squint angle, taIs the azimuth slow time;
the azimuth frequency of the echo signal can be obtained as follows:
Figure BDA0002924787910000052
according to the Doppler center frequency and the Doppler modulation frequency obtained in the step two, a parameter VrAnd thetarThe inversion can be obtained according to the following formula:
Figure BDA0002924787910000053
Figure BDA0002924787910000054
however, due to the one-way nature of passive positioning, the distance R cannot be obtained by the distance-wise matched filtering before the azimuth-wise matched filteringcAnd thus the equivalent speed VrThe estimation of (2) adopts geometric estimation, and the final distance model parameter estimation formula is as follows:
Figure BDA0002924787910000055
Figure BDA0002924787910000056
wherein, VgIs the speed of movement of the radar beam on the earth's surface, VsIs the velocity of the satellite.
Preferably, the method for obtaining the azimuth positioning information in the fourth step is as follows:
discretizing distance search range R1，…Rk,…RRAnd (4) performing azimuth matched filtering according to discrete distance, wherein the dimensionality is R, the obtained data dimensionality is still R multiplied by D, and the constructed matched filter formula is as follows:
h(ta,Rk)＝exp(jπγkta 2)
wherein, taFor azimuthal slow time, gammakIn order to match the frequency of the tuning of the filter,
the equivalent filter constructed in the doppler domain according to the stationary phase principle is:
Figure BDA0002924787910000061
wherein f isaIn the form of an azimuth frequency, the azimuth frequency,
Figure BDA0002924787910000062
λ is the wavelength of the signal and,
the matched filtering result is:
Figure BDA0002924787910000063
wherein, w (t)r,ta) The signal is the signal after the signal passes through the carrier frequency.
Preferably, the method for obtaining the location information of the distance direction by focusing in the step five comprises the following steps:
rearranging the positioning results at different distances according to the distances when matching the filter Rk＝RcWhen the target is located at a distance, the target is focused along the azimuth direction, and the target is defocused at other distances, so that the distance direction of the target can be located.
Preferably, the method for obtaining the two-dimensional positioning information of the target in the sixth step is as follows:
selecting a distance { R 'with smaller interval according to the obtained distance direction positioning information'1，…R'k,…R'RAnd fourthly, performing azimuth matched filtering and distance dimension rearrangement according to the methods in the fourth step and the fifth step to obtain a new more accurate distance positioning result.
The examples are described in connection with the principle shown in fig. 1, where sr(tr,ta) Representing the acquired signal at a frequency fcUsing exp { -j2 π fctaFrequency-off-loading the signal, taThe azimuth slow time.
The method comprises the following steps: the collected signals are processed by the Doppler processing in the slow time domain to obtain time-Doppler data
The dimension of a fast time domain of acquired data is 512, Fourier transform is carried out along a slow time axis, the dimension of a Doppler domain of the data is 4096, so that the obtained time-Doppler two-dimensional data is { data }, the dimension of the time-Doppler two-dimensional data is 512 multiplied by 4096, the signal pulse repetition frequency is 5000Hz, the synthetic aperture time is 0.8192s, and a time-Doppler graph is drawn as shown in FIG. 2;
step two: performing short-time Fourier transform on the signal, and performing time-frequency estimation to obtain Doppler center frequency and Doppler frequency modulation
Performing Doppler parameter estimation, performing short-time Fourier transform of the azimuth direction on the acquired signals to ensure the accuracy of the parameter estimation, performing time-frequency estimation, wherein the window length of the short-time Fourier transform is 128, the step length is 1, the number of data segments is 3969, and performing linear fitting on each segment of data center to obtain the Doppler center frequency fdcAnd Doppler frequency f1r；
Step three: and (3) inverting the low-orbit equivalent squint distance model parameters through the obtained Doppler center frequency and Doppler modulation frequency to obtain the satellite equivalent speed and the equivalent squint angle
Due to the one-way nature of passive positioning, the distance R cannot be obtained by distance-wise matched filtering before the azimuth-wise matched filteringcAnd thus the equivalent speed VrThe estimation adopts geometric estimation, and the final parameter estimation formula of the equivalent squint angle is as follows:
Figure BDA0002924787910000071
Figure BDA0002924787910000072
wherein, VgIs the speed of movement of the radar beam on the earth's surface, VsIs the velocity of the satellite;
step four: carrying out azimuth matching filtering on the signals for multiple times according to the distance to obtain azimuth positioning information
Discretizing distance search range R1，…Rk,…R512}∈[500km,1000km]And the dimensionality is 512, azimuth matched filtering is carried out according to the discrete distance, the dimensionality of the obtained data after matched filtering is 512 multiplied by 4096, and the constructed matched filter formula is as follows:
h(ta,Rk)＝exp(jπγkta 2)
wherein, taFor azimuthal slow time, gammakIn order to match the frequency of the tuning of the filter,
the equivalent filter constructed in the doppler domain according to the stationary phase principle is:
Figure BDA0002924787910000073
wherein f isaIn the form of an azimuth frequency, the azimuth frequency,
Figure BDA0002924787910000074
λ is the wavelength of the signal and,
the matched filtering result is:
Figure BDA0002924787910000081
wherein, w (t)r,ta) The signal is the signal after the signal passes through the carrier frequency;
step five: rearranging the positioning results at different distances according to the distance, and obtaining the positioning information of the distance direction by focusing
Rearranging the positioning results at different distances according to the distances when matching the filter Rk＝RcThen, focusing the distance along the azimuth direction, defocusing other distances, drawing a positioning result graph as shown in fig. 3, obtaining two-dimensional positioning information of the target, and obtaining a positioning error which is about 0.5km and is smaller than the passive positioning error of the single-satellite two-dimensional quadrature phase interferometer through error calculation;
step six: selecting a smaller distance interval according to the distance positioning result, repeating the fourth step and the fifth step, and performing more accurate distance positioning so as to obtain two-dimensional positioning information of the target
Selecting a smaller distance interval according to the distance positioning result, repeating the fourth step and the fifth step, and performing more accurate distance positioning, { R'1，…R'k,…R'512}∈[R0-5km,R0+5km]，R0And obtaining a new more accurate distance direction positioning result for the distance direction information obtained in the step five.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.

Claims (7)

1.一种基于虚拟孔径的星载无源定位方法，其特征在于：包括以下步骤：1. a space-borne passive positioning method based on virtual aperture, is characterized in that: comprise the following steps: 步骤一：对采集到的信号进行慢时间域的多普勒处理，得到时间-多普勒数据；Step 1: Doppler processing in the slow time domain on the collected signal to obtain time-Doppler data; 步骤二：对信号做短时傅里叶变换，进行时频估计，得到多普勒中心频率和多普勒调频率；Step 2: Perform short-time Fourier transform on the signal, perform time-frequency estimation, and obtain the Doppler center frequency and Doppler modulation frequency; 步骤三：通过得到的多普勒中心频率和多普勒调频率对低轨等效斜视距离模型参数进行反演，得到卫星等效速度和等效斜视角；Step 3: Invert the parameters of the low-orbit equivalent strabismus distance model through the obtained Doppler center frequency and Doppler modulation frequency, and obtain the satellite equivalent velocity and equivalent strabismus angle; 步骤四：将信号按距离进行多次方位向匹配滤波，得到方位向定位信息；Step 4: Perform multiple azimuth matching filtering on the signal according to distance to obtain azimuth positioning information; 步骤五：将不同距离处的定位结果按距离重新排列，通过聚焦获得距离向的定位信息；Step 5: Rearrange the positioning results at different distances by distance, and obtain distance-wise positioning information by focusing; 步骤六：根据距离定位结果，选取更小的距离区间段，重复步骤四、步骤五，进行更精确的距离向定位，从而得到目标的二维定位信息。Step 6: According to the distance positioning result, select a smaller distance interval, and repeat steps 4 and 5 to perform more accurate distance direction positioning, thereby obtaining the two-dimensional positioning information of the target. 2.根据权利要求1所述的一种基于虚拟孔径的星载无源定位方法，其特征在于：所述步骤一中得到时间-多普勒数据的方法为，采集到的信号快时间域的维度为R,沿慢时间轴进行傅里叶变换，数据的多普勒域维度为D，故得到的时间-多普勒二维数据为{data},其维度为R×D，信号脉冲重复频率为PRF，则合成孔径时间为D/PRF。2. a kind of spaceborne passive positioning method based on virtual aperture according to claim 1, it is characterized in that: the method for obtaining time-Doppler data in described step 1 is, the signal that collects is fast time domain The dimension is R, the Fourier transform is performed along the slow time axis, and the Doppler domain dimension of the data is D, so the obtained time-Doppler two-dimensional data is {data}, its dimension is R×D, and the signal pulse repeats The frequency is PRF, then the synthetic aperture time is D/PRF. 3.根据权利要求2所述的一种基于虚拟孔径的星载无源定位方法，其特征在于：所述步骤二中得到多普勒中心频率和多普勒调频率的方法为，进行多普勒参数估计，为了保证参数估计的准确性，对采集到的信号做方位向的短时傅里叶变换，进行时频估计，短时傅里叶变换的窗口长度为L，步长为M，则数据段数为
Figure FDA0002924787900000011
对每一段数据中心进行直线拟合得到多普勒中心频率fdc和多普勒调频率f1r。3. a kind of on-board passive positioning method based on virtual aperture according to claim 2, is characterized in that: the method that obtains Doppler center frequency and Doppler frequency modulation frequency in described step 2 is, carry out Doppler Le parameter estimation, in order to ensure the accuracy of parameter estimation, the collected signal is subjected to short-time Fourier transform in the azimuth direction, and time-frequency estimation is performed. The window length of the short-time Fourier transform is L, and the step size is M. Then the number of data segments is
Figure FDA0002924787900000011
The Doppler center frequency f dc and the Doppler modulation frequency f 1r are obtained by linear fitting for each segment of the data center. 4.根据权利要求3所述的一种基于虚拟孔径的星载无源定位方法，其特征在于：所述步骤三中得到卫星等效速度和等效斜视角的方法为，对于星载情况，选用等效斜视距离模型，模型表达式为：4. a kind of on-board passive positioning method based on virtual aperture according to claim 3, is characterized in that: the method that obtains satellite equivalent velocity and equivalent oblique angle of view in described step 3 is, for on-board situation, Using the equivalent strabismus distance model, the model expression is:
Figure FDA0002924787900000021
Figure FDA0002924787900000021
 其中，Rc是波束中心时刻目标的距离，Vr是卫星的等效速度，θr是等效斜视角，ta是方位慢时间；Among them, R c is the distance to the target at the center of the beam, V r is the equivalent velocity of the satellite, θ r is the equivalent oblique angle, and ta is the azimuth slow time; 由此可以得到回波信号的方位向频率：From this, the azimuth frequency of the echo signal can be obtained:
Figure FDA0002924787900000022
Figure FDA0002924787900000022
 根据步骤二中得到的多普勒中心频率和多普勒调频率，参数Vr和θr可以根据如下公式反演得到：According to the Doppler center frequency and Doppler modulation frequency obtained in step 2, the parameters V r and θ r can be obtained by inversion according to the following formulas:
Figure FDA0002924787900000023
Figure FDA0002924787900000023
Figure FDA0002924787900000024
Figure FDA0002924787900000024
 但是由于无源定位的单程性，无法在方位向匹配滤波之前，通过距离向匹配滤波先得到距离Rc，因此等效速度Vr的估计选用几何估计，最终距离模型参数估计公式为：However, due to the one-way nature of passive positioning, the distance R c cannot be obtained through the range matched filter before the azimuth matched filter. Therefore, geometric estimation is used to estimate the equivalent velocity V r . The final distance model parameter estimation formula is:
Figure FDA0002924787900000025
Figure FDA0002924787900000025
Figure FDA0002924787900000026
Figure FDA0002924787900000026
 其中，Vg是雷达波束在地表的移动速度，Vs是卫星的速度。where V g is the moving speed of the radar beam on the surface and V s is the speed of the satellite. 5.根据权利要求4所述的一种基于虚拟孔径的星载无源定位方法，其特征在于：所述步骤四中得到方位向定位信息的方法为，将距离搜索范围进行离散{R1，…Rk,…RR}，维度为R，按离散距离进行方位向匹配滤波，得到的数据维度仍为R×D，构造的匹配滤波器公式为：5. A kind of on-board passive positioning method based on virtual aperture according to claim 4, it is characterized in that: the method for obtaining azimuth positioning information in the described step 4 is, the distance search range is discretized {R 1 , …R k ,…R R }, the dimension is R, the azimuth matched filtering is performed according to the discrete distance, and the obtained data dimension is still R×D. The constructed matched filter formula is: h(ta,Rk)＝exp(jπγkta 2)h(t a , R k )=exp(jπγ k t a 2 ) 其中，ta为方位慢时间，γk为匹配滤波器的调频率，where t a is the azimuth slow time, γ k is the modulation frequency of the matched filter, 按照驻定相位原理在多普勒域构造的等效滤波器为：The equivalent filter constructed in the Doppler domain according to the stationary phase principle is:
Figure FDA0002924787900000031
Figure FDA0002924787900000031
 其中，fa为方位向频率，
Figure FDA0002924787900000032
λ为信号的波长，where f a is the azimuth frequency,
Figure FDA0002924787900000032
λ is the wavelength of the signal, 匹配滤波结果为：The matched filter result is:
Figure FDA0002924787900000033
Figure FDA0002924787900000033
 其中，w(tr,ta)为信号经过去载频后的信号。Among them, w(t r , ta ) is the signal after the signal has been de-carrier frequency. 6.根据权利要求5所述的一种基于虚拟孔径的星载无源定位方法，其特征在于：所述步骤五中通过聚焦获得距离向的定位信息的方法为，将不同距离处的定位结果按距离重新排列，当匹配滤波器Rk＝Rc时，该距离处沿方位向聚焦，其他距离处散焦，由此可对目标的距离向定位信息。6. A kind of on-board passive positioning method based on virtual aperture according to claim 5, it is characterized in that: in described step 5, the method that obtains the positioning information of distance direction by focusing is, Rearranged by distance, when the matched filter R k =R c , the distance is focused along the azimuth direction, and the other distances are defocused, so that the information can be located in the distance direction of the target. 7.根据权利要求6所述的一种基于虚拟孔径的星载无源定位方法，其特征在于：所述步骤六中得到目标的二维定位信息的方法为，根据所得距离向定位信息，选取间隔更小的距离{R'1，…R'k,…R'R}按照步骤四、步骤五所述的方法进行方位向的匹配滤波和距离维的重新排列，得到新的更加精确的距离向定位结果。7. a kind of on-board passive positioning method based on virtual aperture according to claim 6, it is characterized in that: the method that obtains the two-dimensional positioning information of target in described step 6 is, according to gained distance to positioning information, select The distances {R' 1 ,...R' k ,...R' R } with smaller intervals are performed according to the methods described in Steps 4 and 5 to perform azimuth matched filtering and rearrangement of the distance dimension to obtain a new and more accurate distance to the positioning result.
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