A passive radar imaging method based on satellite multipath effect

Abstract

The present invention discloses a passive radar imaging method based on satellite multipath effects, comprising: obtaining a total received signal based on a passive radar geometric model; sequentially performing a Doppler coarse search on the total received signal to obtain a first calibration signal; performing matched filtering on the signal after the first calibration to extract a peak phase to obtain a second calibration signal; locating the second calibration signal to determine the location of a direct signal; performing cancellation processing on the direct signal in the second calibration signal based on the located direct signal, and performing distance alignment on the self-multipath signal in the second calibration signal to obtain an aligned self-multipath signal; performing imaging using the aligned self-multipath signal to obtain an initial self-multipath signal image; and obtaining a final self-multipath signal image based on the initial self-multipath signal image. The present invention is based on a passive radar model, and therefore does not require active emission of electromagnetic waves; only requires a ground receiver to receive electromagnetic signals radiated from a satellite.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar signal processing, and in particular relates to a passive radar imaging method based on satellite multipath effect. Background Art

[0002] A typical bistatic synthetic aperture radar consists of three components: spatially separated antennas for radiating electromagnetic waves and receiving echoes, and a target in the far field of both the transmitter and receiver. Based on a typical bistatic synthetic aperture radar, various bistatic configurations can be created through different transmitter and receiver combinations (spaceborne, airborne, and fixed). This also makes it possible to use passive radar (PR) systems. Passive radars do not radiate electromagnetic signals themselves, but instead use electromagnetic signals reflected from targets to locate and track them.

[0003] During the operation of the satellite, the satellite transmits electromagnetic signals, and the receiver on the ground receives the electromagnetic signals. Since the ground receiver does not directly radiate electromagnetic signals, a passive radar system is formed between the satellite and the ground receiver.

[0004] In the process of receiving satellite signals, in addition to receiving signals that reach the receiver via a straight path, signals are also received from the satellite side leakage, which are reflected by the satellite body and then propagated to the receiver. These reflected signals are superimposed on the direct signal (DS), causing the observed value to deviate from its true value and produce errors. This phenomenon is called the satellite multipath effect (Multi-Path Effect). The multipath effect is not conducive to the satellite completing its own tasks, such as communication, broadcasting, positioning, etc. However, the generation of self-multipath signal (SMS) makes it possible to observe the structure of the satellite body. Self-multipath signal is defined as the multipath signal generated by the transmitter itself.

[0005] Conventional processing for multipath effects is to eliminate its influence and thus improve the accuracy of the observed true value. However, few methods use the information from multipath signals for imaging processing. Summary of the Invention

[0006] To address the aforementioned issues in the existing technology, the present invention proposes a passive radar imaging method based on satellite self-multipath effects. This method utilizes received electromagnetic signals from satellites to synchronize the satellites and filter out direct signals from echo signals. The remaining signals, including the self-multipath effects, are then used to reconstruct the satellite's geometry. The technical problem addressed by the present invention is achieved through the following technical solutions:

[0007] A passive radar imaging method based on satellite multipath effect, the passive radar imaging method comprising:

[0008] Acquire a total received signal based on a passive radar geometric model, wherein the total received signal includes a self-multipath signal and a direct signal;

[0009] performing a coarse Doppler search on the total received signal in sequence to obtain a first calibration signal;

[0010] Performing matched filtering on the signal after the first calibration to extract the peak phase to obtain a second calibration signal;

[0011] Positioning the second calibration signal to determine the position of the direct signal;

[0012] performing cancellation processing on the direct signal in the second calibration signal based on the located direct signal, and performing distance alignment on the self-multipath signal in the second calibration signal to obtain an aligned self-multipath signal;

[0013] Performing imaging using the aligned self-multipath signals to obtain an initial self-multipath signal image;

[0014] A final self-multipath signal image is obtained based on the initial self-multipath signal image.

[0015] In one embodiment of the present invention, the total received signal is:

[0016]

[0017] Among them, s r (t,u m ) is the total received signal, s d (t,u m ) is the direct signal, δ k is the combination of the scattering coefficient corresponding to the kth scattering point and its corresponding propagation attenuation, s[·] is the transmitted signal, t is the fast time, u m is the slow time when the receiver receives the mth pulse, r b (u m ) is the slow time u m At the moment, the distance between the phase center of the satellite and the receiver, r(u m ) is the propagation distance of the kth scattering point, r k is the distance between the transmitter phase center and the kth scattering point, x k is the x-axis coordinate of the kth scattering point, y k is the y-axis coordinate of the kth scattering point, c is the speed of light, j represents the complex signal, φ N (u m) is the combination of phase modulation by the communication information and noise from the channel, f c is the center frequency of the transmitted signal, f d (u m ) is the Doppler frequency due to satellite motion, w = RΩ0 / H, Ω0 is the angular velocity around the center of the Earth, R is the radius of the Earth, and H is the satellite altitude;

[0018] The propagation distance of the kth scattering point is:

[0019] r(u m )=r b (u m )+r k +x k sinθ(u m )+y k cosθ(u m )

[0020] The direct signal is:

[0021] s d (t,u m )=s(tr b (u m ) / c)·exp[-j2πf c r b (u m ) / c]·exp[-j2πf d (u m ) / c]·exp[jφ N (u m )]

[0022] Where θ is the angle between the satellite axis and the line between the receiver and the satellite, φ N (u m ) is a combination of phase modulation by the communication information and noise from the channel.

[0023] In one embodiment of the present invention, the step of performing a coarse Doppler search on the total received signal to obtain a first calibration signal includes:

[0024] Within a preset frequency range, compensating the Doppler phase of the total received signal once at every set frequency to obtain a compensated signal;

[0025] The phase with the largest peak value in the pulse compression result of the compensated signal is taken as the first calibration signal.

[0026] In one embodiment of the present invention, the step of performing matched filtering on the signal after the first calibration to extract the peak phase to obtain the second calibration signal includes:

[0027] Performing matched filtering on the first calibrated signal using a reference signal to obtain a matched filtered signal;

[0028] The phase with the largest peak value in the pulse compression result of the matched filtered signal is extracted as the second calibration signal.

[0029] In one embodiment of the present invention, the step of positioning the second calibration signal to determine the positioning of the direct signal includes:

[0030] The second calibration signal is subjected to super-resolution processing in the distance dimension to determine the positioning of the direct signal.

[0031] In one embodiment of the present invention, the aligned self-multipath signal is:

[0032]

[0033] Among them, δ k is the combination of the scattering coefficient corresponding to the kth scattering point and its corresponding propagation attenuation, s[·] is the transmitted signal, t is the fast time, r k is the distance between the transmitter phase center and the kth scattering point, x k is the x-axis coordinate of the kth scattering point, y k is the y-axis coordinate of the kth scattering point, w=RΩ0 / H, Ω0 is the angular velocity around the center of the earth, R is the radius of the earth, H is the height of the satellite, u m is the slow time when the receiver receives the mth pulse, c is the speed of light, f c is the center frequency of the transmitted signal.

[0034] In one embodiment of the present invention, the step of performing imaging using the aligned self-multipath signals to obtain an initial self-multipath signal image includes:

[0035] Performing a two-dimensional inverse fast Fourier transform on the aligned self-multipath signal to obtain an initial self-multipath signal image.

[0036] In one embodiment of the present invention, the initial imaging result of a single scattering point in the multipath signal image is:

[0037] I(d k ,x k )=∫∫s c (f,u m )·exp[j2π(f c +f)x k wu m / c+j2πfd k / c]du m df

[0038] Among them, s c (f,u m ) is the frequency domain corresponding to the multipath signal, f is, d k for.

[0039] In one embodiment of the present invention, the step of obtaining the final self-multipath signal image based on the initial self-multipath signal image includes:

[0040] Based on d k =r k +y k , adjusting the initial self-multipath signal image to obtain the final self-multipath signal image, wherein the position of a single scattering point in the final self-multipath signal image is:

[0041]

[0042] The position of a single scattering point in the final self-multipath signal image is (x k ,y k ,r k ).

[0043] In one embodiment of the present invention, the step of obtaining the final self-multipath signal image based on the initial self-multipath signal image includes:

[0044] The initial self-multipath signal image is processed using a back-projection algorithm to obtain the final self-multipath signal image, which is:

[0045]

[0046] Among them, I c (y k ,x k ) is the final self-multipath signal image, s k (u m ) is the compression signal in the range direction, is the azimuth matched filter;

[0047] The compression signal in the distance direction is:

[0048] s k (u m )=s c [(r k +y k ) / c,u m ]

[0049] The azimuth matched filter is:

[0050]

[0051] Among them, s c [·] is the frequency domain corresponding to the self-multipath signal.

[0052] Beneficial effects of the present invention:

[0053] The present invention proposes a passive radar imaging method based on satellite self-multipath effects. This method utilizes electromagnetic signals received from satellites to synchronize the satellites. A passive radar geometric model is first established. A coarse and fine calibration is then performed on the total received signal, which includes both the self-multipath and direct signals. The location of the direct signal is then determined using a second calibration signal after fine calibration, thereby filtering the direct signal from the total received signal. The remaining signals containing the self-multipath effects are then range-aligned, and the satellite geometry is reconstructed using the range-aligned signals. Thus, the present invention utilizes self-multipath signals to reconstruct the satellite geometry. This method does not require active electromagnetic wave radiation from the ground. Instead, it receives electromagnetic waves radiated by the satellite and analyzes the self-multipath signals therein to image the target satellite's geometry. This imaging method achieves high-resolution imaging in azimuth by increasing the observation time.

[0054] This invention is based on a passive radar model, eliminating the need for active electromagnetic wave transmission. Instead, ground-based receivers receive electromagnetic signals radiated from satellites for subsequent processing. Building on the passive radar model, this invention effectively utilizes the self-multipath effect of satellites, enabling not only the spatial location of a target satellite but also information about its geometric structure derived from the self-multipath signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is a flow chart of a passive radar imaging method based on satellite multipath effect provided by an embodiment of the present invention;

[0056] Figure 2 1 is a geometric diagram of a self-multipath-passive radar system provided by an embodiment of the present invention;

[0057] Figure 3 is a geometric diagram of an imaging process provided by an embodiment of the present invention;

[0058] Figure 4 It is an abstract model diagram provided by an embodiment of the present invention;

[0059] Figure 5 This is a flow chart of Doppler estimation provided by an embodiment of the present invention;

[0060] Figure 6This is a diagram of an accurate Doppler experiment result provided by an embodiment of the present invention;

[0061] Figure 7 1 is a comparison diagram of two direct waves eliminated from multipath signals and non-eliminated direct waves set in an embodiment of the present invention;

[0062] Figure 8 This is a recovery result diagram of a simple satellite model after processing provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0063] The present invention will be further described in detail below with reference to specific examples, but the embodiments of the present invention are not limited thereto.

[0064] Example 1

[0065] See Figure 1 , Figure 1 1 is a flow chart of a passive radar imaging method based on satellite multipath effect provided by an embodiment of the present invention. The present invention provides a passive radar imaging method based on satellite multipath effect, and the passive radar imaging method includes:

[0066] Step 1: Obtain a total received signal based on a passive radar geometric model. The total received signal includes a self-multipath signal and a direct signal.

[0067] First, a passive radar geometric model based on satellite self-multipath effect is established. The geometric diagram of the self-multipath-passive radar model is as follows: Figure 2 As shown, the transmitter and the target are satellites, and the receiver is located at a fixed position on the ground for receiving direct signals radiated from the satellite and multipath signals.

[0068] like Figure 3 As shown in the figure, the satellite is in uniform circular motion during the entire imaging process. Without loss of generality, it is assumed that the midpoint of the satellite's trajectory is exactly above the receiver, and the satellite's trajectory, the receiver's position, and the geographic center are coplanar. Its angular velocity around the center of the Earth is Ω0, and a = Ω0u is defined. m is the angle of the satellite rotation, where u m is the slow time when the receiver receives the mth pulse. The angle between the satellite axis and the line between the receiver and the satellite is defined as θ. Figure 3 In the yellow triangle, according to the law of cosines, the distance between the satellite and the receiver is: Furthermore, θ can be expressed by the sine theorem as: θ(u m )≈sinθ(u m )=RΩ0u m / H, R is the radius of the earth, H is the height of the satellite. Define w=RΩ0 / H, then sinθ(um )≈wu m , cosθ(u m )≈1-θ(u m ) 2 / 2.

[0069] Afterwards, the direct signal is modeled, and the generation mechanism of the self-multipath signal is analyzed and modeled. Finally, the total received signal is obtained, which includes the self-multipath signal and the direct signal.

[0070] Figure 4 It is an abstract geometric model of a multipath-passive radar system. Its imaging process is similar to that of inverse synthetic aperture radar. The range resolution is achieved by matched filtering of the received signal, and the azimuth resolution is achieved by the relative attitude angle between the receiver and the target satellite. The line of sight between the receiver and the satellite's centroid is defined as the Y axis, as shown in the figure. Figure 4 As shown in the figure, the X-axis is defined as the normal vector of the Y-Ω plane, the Z-axis is defined as the normal vector of the XY plane, and Ω is the total rotation vector of the target. The Y-axis component does not affect the resolution of the azimuth angle.

[0071] Depend on Figure 4 The geometric relationship shown in the figure shows that, unlike the conventional inverse synthetic aperture model, the self-multipath-passive radar model consists of a near-field (from the satellite phase center to the scattering point) and a far-field (from the scattering center to the receiver). The propagation distance of the kth scattering point is:

[0072] r(u m )=r b (u m )+r k +x k sinθ(u m )+y k cosθ(u m ) (1)

[0073] Among them, r(u m ) is the propagation distance of the kth scattering point, r b (u m ) is the slow time u m At time t, the distance between the phase center of the satellite and the receiver is r k is the distance between the transmitter phase center and the kth scattering point, x k is the x-axis coordinate of the kth scattering point, y k is the y-axis coordinate of the kth scattering point.

[0074] The transmitted signal is expressed as s(t), and the direct wave signal component in the total received signal is:

[0075]

[0076] Among them, s d (t,u m ) is the direct signal, s[·] is the transmitted signal, t is the fast time, c is the speed of light, j represents the complex signal, φ N (u m ) is the combination of phase modulation by the communication information and noise from the channel, f c is the center frequency f of the transmitted signal d (u m ) is the Doppler frequency due to satellite motion.

[0077] Then the total received signal can be expressed as:

[0078]

[0079] Among them, s r (t,u m ) is the total received signal, δ k is the combination of the scattering coefficient corresponding to the kth scattering point and its corresponding propagation attenuation.

[0080] Step 2: Perform a coarse Doppler search on the total received signal to obtain a first calibration signal.

[0081] In a specific embodiment, step 2 may include:

[0082] Step 2.1, within a preset frequency range, the Doppler phase of the total received signal is compensated once at every set frequency to obtain a compensated signal;

[0083] Step 2.2: Take the phase with the largest peak value in the pulse compression result of the compensated signal as the first calibration signal to complete the coarse calibration of the Doppler.

[0084] For example, the Doppler phase is compensated every 100 Hz within the range of -1000 to 1000 Hz, and the phase with the largest peak value of the pulse compression result after compensation is taken as the first calibration signal of the coarse calibration.

[0085] Step 3: Perform matched filtering on the signal after the first calibration to extract the peak phase to obtain a second calibration signal.

[0086] In a specific embodiment, step 3 may include:

[0087] Step 3.1: Use the reference signal to perform matched filtering on the signal after the first calibration to obtain a matched filtered signal.

[0088] Optionally, the reference signal is a linear frequency modulation signal.

[0089] Step 3.2: Extract the phase with the largest peak value in the pulse compression result of the matched filtered signal as the second calibration signal to complete the precise calibration of the Doppler.

[0090] The specific processing flow of step 2 and step 3 is as follows Figure 5 As shown in Figure 1, this step mainly extracts the peak phase after matching filtering the received signal. Usually, the process from step 2 to step 3 will go through a typical three-step Doppler tracking, from coarse to medium to fine frequency tracking, and finally complete the precise calibration of the Doppler modulation term. After processing 10,000 snapshots (0.1s), the finely calibrated Doppler is as follows: Figure 6 As shown, the error is basically within 0.5Hz.

[0091] Step 4: Position the second calibration signal to determine the position of the direct signal.

[0092] Here, the positioning of the second calibration signal is completed, and the position of the positioned second calibration signal is the position of the direct signal, because the power of the direct signal is the strongest.

[0093] Specifically, the direct signal is located by super-resolution processing of the distance dimension of the second calibration signal. The discretization of formula (2) can be expressed as:

[0094] s=w T σ+n (4)

[0096] Among them, w T = [w(p), w(p-1), …, w(p-P+1)] is the distance measurement matrix, p is a discrete time series, and P is chosen so that the distance measurement matrix includes the direct wave range of the satellite. σ is a sparse vector representing the scattering characteristics of the target at different range grids, and n is the noise. This then becomes a sparse reconstruction problem. Currently, there are various sparse reconstruction methods, with different grid widths set according to different accuracy requirements.

[0097] After the direct signal is located, since the signal form is known, the phase of the direct signal can be directly obtained from the position of the direct signal, thereby completing the reconstruction of the direct signal.

[0098] Step 5: Based on the located direct signal, cancel the direct signal in the second calibration signal, and perform distance alignment on the self-multipath signal in the second calibration signal to obtain an aligned self-multipath signal.

[0099] In other words, after locating the direct signal, its phase can be accurately extracted and, after Doppler phase compensation, its cancellation is completed. After direct signal cancellation, envelope alignment in the range dimension is completed using the direct signal as a reference.

[0100] After completing the reconstruction of the direct wave signal in step 5, the direct wave can be canceled through various methods such as frequency domain and time domain. The self-multipath signal after cancellation and distance alignment is expressed as:

[0101]

[0102] Among them, s m (t,u m ) is the self-multipath signal after alignment.

[0103] The pure self-multipath signal can be expressed as:

[0104]

[0105] in, is the convolution, and δ(·) is the impulse function.

[0106] Step 6: Use the aligned self-multipath signals to perform imaging to obtain an initial self-multipath signal image.

[0107] Specifically, a two-dimensional inverse fast Fourier transform is performed on the aligned self-multipath signal to obtain an initial self-multipath signal image.

[0108] After processing in steps 5 and 6, a pure self-multipath signal in the time domain can be obtained. The time domain expression corresponding to the self-multipath signal is:

[0109]

[0110] Among them, s c (t,u m ) is the time domain corresponding to the multipath signal, s a [·] is the sinc function.

[0111] The frequency domain expression corresponding to the multipath signal is:

[0112]

[0113] Among them, s c (f,u m ) is the frequency domain corresponding to the multipath signal.

[0114] The above frequency domain expression is similar to the ISAR signal model, so the two-dimensional inverse fast Fourier transform can be applied to generate the initial image. The imaging result of a single scattering point can be written as:

[0115] I(d k ,x k )=∫∫s c (f,u m )·exp[j2π(fc +f)x k wu m / c+j2πfd k / c]du m df (9)

[0116] Among them, I(d k ,x k ) is the imaging result of the scattering point k.

[0117] Step 7: Obtain a final self-multipath signal image based on the initial self-multipath signal image.

[0118] Because the imaging result obtained by the two-dimensional inverse fast Fourier transform in step 6 is still deformed, it is necessary to adjust the initial self-multipath signal image obtained in step 6 to obtain the final self-multipath signal image. In this embodiment, two methods for adjusting the deformation of the initial self-multipath signal image are provided.

[0119] The first method is: based on d k =r k +y k , the initial self-multipath signal image is adjusted to obtain the final self-multipath signal image. The position of a single scattering point in the final self-multipath signal image is:

[0120]

[0121] Among them, the position of a single scattering point in the final self-multipath signal image is (x k ,y k ,r k ), thus, the true position of the self-multipath signal is obtained, and formula (10) is substituted into formula (9) to obtain the final self-multipath signal image.

[0122] The second method is to use a back-projection algorithm to process the initial self-multipath signal image to obtain the final self-multipath signal image.

[0123] Here, the back projection algorithm is used for processing. The main idea is to grid the imaging area into a two-dimensional grid in (x, y), each grid contains coordinate information (x k ,y k ,r k ).

[0124] Among them, the compression signal in the range direction can be extracted as:

[0125] s k (u m )=s c [(r k +y k) / c,u m ] (11)

[0126] Among them, s c [·] is the frequency domain corresponding to the self-multipath signal.

[0127] The matched filter in azimuth is:

[0128]

[0129] Therefore, the self-multipath signal image can be expressed as:

[0130]

[0131] Therefore, formula (13) is the final imaging result obtained using the second method.

[0132] like Figure 7 As shown, Figure 7 The reconstruction results of the two self-multipath signals are shown in Figure 2. Figure 8 As shown. Among them, Figure 7 The first figure in the figure shows the result of not eliminating the direct wave, since the multipath signal is masked by the side lobes of the direct wave. Figure 7 The second figure in the figure shows the reconstruction result of the self-multipath signal after eliminating the direct wave. The two self-multipath signals are distinguished. The difference in amplitude is caused by the difference in intensity between the direct wave and the self-multipath signal. The distance dimension is limited by the bandwidth and cannot be completely and effectively distinguished. The azimuth resolution is limited by the rotation angle. When the rotation angle is 1.5° and the coherent accumulation time is 1 minute, two scattering points 7 meters apart can be distinguished using the reconstruction of the self-multipath signal. Similarly, Figure 8 It can distinguish targets in azimuth. With the increase of accumulation time and satellite rotation angle, higher resolution can be achieved. The distance dimension is limited by bandwidth, and it is impossible to distinguish the scattering points on the satellite in the distance dimension under the size of the satellite.

[0133] The present invention proposes a passive radar imaging method based on satellite self-multipath effects. This method utilizes electromagnetic signals received from satellites to synchronize the satellites. A passive radar geometric model is first established. A coarse and fine calibration is then performed on the total received signal, which includes both the self-multipath and direct signals. The location of the direct signal is then determined using a second calibration signal after fine calibration, thereby filtering the direct signal from the total received signal. The remaining signals containing the self-multipath effects are then range-aligned, and the satellite geometry is reconstructed using the range-aligned signals. Thus, the present invention utilizes self-multipath signals to reconstruct the satellite geometry. This method does not require active electromagnetic wave radiation from the ground. Instead, it receives electromagnetic waves radiated by the satellite and analyzes the self-multipath signals therein to image the target satellite's geometry. This imaging method achieves high-resolution imaging in azimuth by increasing the observation time.

[0134] This invention is based on a passive radar model, eliminating the need for active electromagnetic wave transmission. Instead, ground-based receivers receive electromagnetic signals radiated from satellites for subsequent processing. Building on the passive radar model, this invention effectively utilizes the self-multipath effect of satellites, enabling not only the spatial location of a target satellite but also information about its geometric structure derived from the self-multipath signals.

[0135] In the description of this specification, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification.

[0136] Although the present application is described herein in conjunction with various embodiments, in the process of implementing the claimed application, those skilled in the art can understand and implement other changes to the disclosed embodiments by reviewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude multiple situations. A single processor or other unit can implement several functions listed in the claims. Certain measures are recorded in different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

[0137] The above is a further detailed description of the present invention in conjunction with specific preferred embodiments, and the specific implementation of the present invention should not be considered to be limited to these descriptions. For those skilled in the art of the present invention, without departing from the concept of the present invention, several simple deductions or substitutions can be made, which should be considered to fall within the scope of protection of the present invention.

Claims

1. A passive radar imaging method based on satellite multipath effect, characterized in that: The passive radar imaging method comprises: Obtaining a total received signal based on a passive radar geometric model, wherein the total received signal includes a self-multipath signal and a direct signal, wherein the self-multipath signal is a multipath signal of electromagnetic waves emitted by a satellite, which is reflected by the satellite body and received by the radar on the ground; performing a coarse Doppler search on the total received signal in sequence to obtain a first calibration signal; Performing matched filtering on the first calibration signal to extract a peak phase to obtain a second calibration signal; Positioning the second calibration signal to determine the position of the direct signal; performing cancellation processing on the direct signal in the second calibration signal based on the located direct signal, and performing distance alignment on the self-multipath signal in the second calibration signal to obtain an aligned self-multipath signal; Performing imaging using the aligned self-multipath signals to obtain an initial self-multipath signal image; A final self-multipath signal image is obtained based on the initial self-multipath signal image.

2. The passive radar imaging method based on satellite multipath effect according to claim 1, characterized in that: The total received signal is: in, is the total received signal, For direct signals, For the The combination of the scattering coefficient corresponding to each scattering point and its corresponding propagation attenuation, To transmit the signal, For quick time, The receiver receives the The slow time of a pulse, For slow time At time , the distance between the phase center of the satellite and the receiver, For the The propagation distance of a scattering point, The phase center of the transmitter is The distance between the scattering points, , For the scattering points x Axis coordinates, For the scattering points y Axis coordinates, is the speed of light, represents a complex signal, is the combination of phase modulation by the communication information and noise from the channel, is the center frequency of the transmitted signal, is the Doppler frequency due to satellite motion, , is the angular velocity around the center of the Earth, is the radius of the Earth, is the satellite altitude; The said The propagation distance of a scattering point is: The direct signal is: in, is the angle between the satellite axis and the line between the receiver and the satellite, It is a combination of phase modulation by the communication information and noise from the channel.

3. The passive radar imaging method based on satellite multipath effect according to claim 1, characterized in that: The step of performing a coarse Doppler search on the total received signal to obtain a first calibration signal comprises: Within a preset frequency range, compensating the Doppler phase of the total received signal once at every set frequency to obtain a compensated signal; The phase with the largest peak value in the pulse compression result of the compensated signal is taken as the first calibration signal.

4. The passive radar imaging method based on satellite multipath effect according to claim 1, characterized in that: The step of performing matched filtering on the first calibration signal to extract the peak phase to obtain the second calibration signal includes: Performing matched filtering on the first calibration signal using a reference signal to obtain a matched filtered signal; The phase with the largest peak value in the pulse compression result of the matched filtered signal is extracted as the second calibration signal.

5. The passive radar imaging method based on satellite multipath effect according to claim 1, characterized in that: The step of positioning the second calibration signal to determine the positioning of the direct signal comprises: The second calibration signal is subjected to super-resolution processing in the distance dimension to determine the positioning of the direct signal.

6. The passive radar imaging method based on satellite multipath effect according to claim 1, characterized in that: The aligned self-multipath signal is: in, For the The combination of the scattering coefficient corresponding to each scattering point and its corresponding propagation attenuation, To transmit the signal, For quick time, The phase center of the transmitter is The distance between the scattering points, , For the scattering points x Axis coordinates, For the scattering points y Axis coordinates, , is the angular velocity around the center of the Earth, is the radius of the Earth, is the satellite altitude, The receiver receives the The slow time of a pulse, is the speed of light, is the center frequency of the transmitted signal.

7. The passive radar imaging method based on satellite multipath effect according to claim 6, characterized in that: The step of performing imaging using the aligned self-multipath signals to obtain an initial self-multipath signal image comprises: Performing a two-dimensional inverse fast Fourier transform on the aligned self-multipath signal to obtain an initial self-multipath signal image.

8. The passive radar imaging method based on satellite multipath effect according to claim 6, characterized in that: The imaging result of a single scattering point in the initial self-multipath signal image is: in, is the frequency domain signal corresponding to the self-multipath signal, Indicates frequency, .

9. The passive radar imaging method based on satellite multipath effect according to claim 8, characterized in that: The step of obtaining a final self-multipath signal image based on the initial self-multipath signal image comprises: based on , adjusting the initial self-multipath signal image to obtain the final self-multipath signal image, wherein the position of a single scattering point in the final self-multipath signal image is: The position of a single scattering point in the final self-multipath signal image is .

10. The passive radar imaging method based on satellite multipath effect according to claim 8, characterized in that: The step of obtaining a final self-multipath signal image based on the initial self-multipath signal image comprises: The initial self-multipath signal image is processed using a back-projection algorithm to obtain the final self-multipath signal image, which is: in, is the final self-multipath signal image, is the compression signal in the range direction, is the azimuth matched filter; The compression signal in the distance direction is: The azimuth matched filter is: in, is the frequency domain signal corresponding to the multipath signal.

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