An azimuth decimation method based on navigation satellite bistatic InSAR

Abstract

The present invention discloses a method for azimuth downsampling based on bistatic InSAR of navigation satellites. Under the premise of ensuring the amplitude, phase and accuracy of the imaging result, this method segments the working trajectory of the navigation satellite, and uses the satellite position corresponding to the middle moment of each trajectory segment to replace the whole of this trajectory segment to calculate the distance between the navigation satellite and the scene target, and then obtains the phase compensation factor required for back projection. The echoes within each sub-segment are coherently superimposed, and the obtained result is regarded as the result under the entire working trajectory for back projection imaging. The invention reduces the amount of data for the system to synthesize in the azimuth direction to obtain the result, thereby reducing the communication data volume and enhancing the real-time signal processing ability of the system.

Description

Technical Field

[0001] The present invention belongs to the technical field of bistatic synthetic aperture radar, and particularly relates to an azimuth downsampling method based on a bistatic InSAR (Differential Interferometric Synthetic Aperture Radar System) of navigation satellites. Background Art

[0002] Compared with traditional airborne systems or spaceborne systems, the navigation satellite bistatic differential interferometric synthetic aperture radar system (GNSS-InSAR, Differential Interferometric Bistatic Synthetic Aperture Radar Based on Global Navigation Satellite System) uses on-orbit navigation satellites as external radiation sources and deploys stationary receiving mechanisms near the ground to form a bistatic SAR system, which has the advantages of high data rate, low cost, and easy deployment. At the same time, the navigation satellite constellation resources are rich, such as the on-orbit Beidou, GPS, GLONASS, Galileo, etc., and have the characteristics of global coverage and short-time revisit, and can provide multi-angle data sets and rich spatio-temporal resources. Therefore, this system can be used for various deformation monitoring commonly found in natural disasters. However, since the working altitude of the navigation satellite is more than 20,000 kilometers away from the ground, in order to obtain an imaging result with a relatively high azimuth resolution, a synthetic aperture accumulation time of about 100 seconds is required, which is two orders of magnitude higher than that of traditional systems. Therefore, the communication data rate is very large, and the hardware requirements are relatively high, which limits the real-time signal processing ability of this system. Summary of the Invention

[0003] In view of this, the present invention provides an azimuth downsampling method based on a bistatic InSAR of navigation satellites, which can improve the real-time signal processing ability.

[0004] To achieve the above object, the technical solution of the present invention is as follows:

[0005] An azimuth downsampling method based on a bistatic InBSAR of navigation satellites segments the working trajectory of the navigation satellite, and takes the position of the navigation satellite corresponding to the central moment of each segment of the trajectory as the satellite position corresponding to the whole segment of the trajectory; calculates the distance quantity corresponding to the imaging target by using the satellite position of each segment of the trajectory; constructs a phase compensation factor by using the distance quantity and performs phase compensation on the corresponding small segment of the trajectory; multiplies the collected data in all sub-segments by the corresponding sub-segment compensation factors and then superimposes them, and regards the obtained result as the total result of the entire navigation satellite trajectory for back-projection imaging.

[0006] Among them, constructing the phase compensation factor of each sub-segment by using the calculated distance quantity specifically includes:

[0007] Let the position at the scene center moment be T0 For the m-th moment, the corresponding bistatic range difference is ΔR = R m - R 0 , where R m is the distance between the m-th trajectory segment and the center of the monitoring scene, and R 0 is the distance between the position at the scene center moment and the center of the monitoring scene; the phase compensation factor for each moment is: where j is the imaginary unit and λ is the wavelength of the system transmitted signal.

[0008] Among them, the specific method for calculating the distance corresponding to the imaging target using the satellite position of each trajectory segment is: in each sub-segment, according to the prior trajectory information, calculate the distance between each real pulse sampling moment and the scene center.

[0009] Among them, the specific method for multiplying and superimposing the acquired data in all sub-segments with the corresponding sub-segment compensation factors is:

[0010] Multiply the data in each sub-segment by the corresponding compensation factor and then accumulate them, thereby obtaining a total result with a data volume of n, and regard this result as the output corresponding to the total trajectory, where n is the amount of acquired data in a sub-segment.

[0011] Among them, when segmenting the working trajectory of the navigation satellite, ensure that when comparing the imaging result obtained after segmentation with the imaging result before segmentation, the amplitude error is less than 1%, and the phase error is less than 0.5 degrees.

[0012] Beneficial Effects

[0013] 1. Aiming at the limitation of the GNSS-InSAR system in real-time signal processing ability, the present invention merges the working trajectories of navigation satellites to reduce the amount of transmitted data. Specifically, the entire synthetic aperture time is segmented, and within each sub-segment, phase compensation is performed according to the position of the scene center and coherent superposition is carried out. The spatial variability of the scene is ignored within the sub-segment, reducing the communication data volume of the bistatic differential interferometric SAR system of navigation satellites and enhancing the real-time signal processing ability.

[0014] 2. The present invention performs the original BP processing for different sub-segments to ensure the phase quality of the final image. Through sub-segment processing, based on the known trajectory information, phase compensation can be carried out relatively quickly, realizing fast processing within the sub-segment.

[0015] 3. In each sub-segment of the azimuth data of the present invention, the pulse compression result is only output once, greatly reducing the communication data volume and further enhancing the real-time signal processing ability of the system. Description of the Drawings

[0016] Figure 1 is the azimuth downsampling processing flow of the embodiment cited in the present invention.

[0017] Figure 2 It is the azimuth downsampling imaging result of 10 times the embodiment of the present invention.

[0018] Figure 3 It is the phase error of the azimuth downsampling result of 10 times the embodiment of the present invention.

[0019] Figure 4 It is the azimuth downsampling imaging result of 1000 times the embodiment of the present invention.

[0020] Figure 5 It is the phase error of the azimuth downsampling imaging of 1000 times the embodiment of the present invention. Detailed implementation manners

[0021] The present invention will be described in detail below with reference to the accompanying drawings and by way of examples.

[0022] The present invention is an azimuth downsampling rate method based on a navigation satellite bistatic differential interferometric synthetic aperture radar system, which specifically includes the following steps:

[0023] Step 1: Segment the working trajectory of the navigation satellite, and use the position of the navigation satellite corresponding to the central moment of each sub-segment trajectory as the satellite position corresponding to the sub-segment. Specifically:

[0024] Suppose a total of s position quantities are obtained during the working time of a certain navigation satellite, and they are divided into i segments. Among them, the segmentation basis is that the amplitude error of the final imaging result is lower than 0.1%, and the phase error is less than 0.5 degrees. The number of trajectories included in each segment is batch_size, where batch_size = s / i. Then the corresponding trajectory of the m-th segment is T m =(x k , y k , z k ), where k = (m - 1)·batch_size + batch_size / 2.

[0025] Step 2: In each sub-segment, calculate the distance between each real pulse sampling moment and the scene center according to the prior trajectory information. Specifically:

[0026] Let the position coordinates of the monitoring scene center P be (x p , y p , z p ). Then the distance between the m-th segment trajectory and the grid point P is R m =|T m -P|.

[0027] Step 3: Use the distance calculated in Step 2 to construct the phase compensation factor of each sub-segment. Specifically:

[0028] Let the position of the scene center at a certain moment be \(T\). 0 For the \(m\)-th moment, the corresponding bistatic range difference is \(\Delta R = R\) m - \(R\) 0 , where \(R\) m is the distance between the \(m\)-th trajectory segment and the scene center, and \(R\) 0 is the distance between the position of the scene center at a certain moment and the scene center. Furthermore, the phase compensation factor for each moment is: where \(j\) is the imaginary unit and \(\lambda\) is the wavelength of the system transmitted signal.

[0029] Step 4: Multiply the acquired data in all sub - segments by the corresponding sub - segment compensation factors and then sum them up. Regard the obtained result as the total result of the entire navigation star trajectory for back - projection imaging. Specifically:

[0030] Suppose there are \(m\) sub - segments in a trajectory and the amount of acquired data in one sub - segment is \(n\). Multiply the data in each sub - segment by the corresponding compensation factor and then sum them up. Thus, a total result with a data volume of \(n\) is obtained, and this result is regarded as the output corresponding to the total trajectory.

[0031] In this embodiment, according to the parameters in Table 1, the echo data of the Beidou prn13 satellite in a certain area of Changshu is processed, and the azimuth accumulation time is 750 seconds. Azimuth down - sampling by 10 times and azimuth down - sampling by 1000 times are respectively carried out. The relevant evaluation indexes of the imaging results of azimuth down - sampling by 10 times and azimuth down - sampling by 1000 times are shown in Table 2.

[0032] Table 1

[0033] Parameter Value Navigation satellite BeiDou system - prn13 Bandwidth 10.23 MHz Center frequency 1268.52 MHz Sampling frequency 31 MHz Synthetic aperture time 750s Pulse repetition time 1 ms Synthetic aperture time 2.5s

[0034] Table 2

[0035] Azimuth down - sampling ratio Signal - to - noise ratio (dB) Two - dimensional resolution (m * m) <![CDATA[3dB resolution cell area (m 2 )]]> 10 40.70 24.41*5.66m 119 1000 40.78 24.41*5.66m 120

[0036] In Table 2, both types of azimuth down - sampling schemes have almost no influence on the imaging results. Therefore, within the allowable error range, this azimuth down - sampling scheme will not affect the subsequent deformation inversion accuracy. The imaging result of 10 - fold down - sampling is as shown in Figure 2 , and the phase error is as shown in Figure 3 . The imaging result of 1000 - fold down - sampling is as shown in Figure 4 , and the phase error is as shown in Figure 5 . Their average phase errors are respectively: - 1.6e7, - 3.4e7, and the maximum values are respectively: 0.0437, 0.1029.

[0037] In summary, the above are only the preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An azimuth decimation method based on bistatic InSAR of navigation satellites, characterized in that, segment the working trajectory of the navigation satellite, and use the position of the navigation satellite corresponding to the central moment of each segment of the trajectory as the satellite position corresponding to the whole segment of the trajectory; calculate the distance corresponding to the imaging target using the satellite position of each segment of the trajectory; construct a phase compensation factor using the distance and perform phase compensation on the corresponding small segment of the trajectory; multiply the acquired data in all sub-segments by the corresponding sub-segment compensation factors and then superimpose them, and regard the obtained result as the total result of the entire navigation satellite trajectory for back-projection imaging; construct a phase compensation factor for each sub-segment using the calculated distance, specifically: Let the position of the scene center at time T be 0 , for the m-th moment, the corresponding bistatic range difference is ΔR = R m -R 0 , where R m is the distance between the m-th trajectory segment and the scene center of the monitoring scene, and R 0 is the distance between the position at the scene center time and the scene center of the monitoring scene; the phase compensation factor for each moment is: where j is the imaginary unit and λ is the wavelength of the system transmitted signal.

2. The azimuth decimation method according to claim 1, characterized in that, the specific method for calculating the distance corresponding to the imaging target using the satellite position of each segment of the trajectory is: in each sub-segment, calculate the distance between each real pulse sampling moment and the center of the scene according to the prior trajectory information.

3. The azimuth decimation method according to any one of claim 1, characterized in that, the specific method for multiplying and superimposing the acquired data in all sub-segments by the corresponding sub-segment compensation factors is: multiply the data in each sub-segment by the corresponding compensation factor and then accumulate them, so as to obtain a total result with a data volume of n, and regard this result as the output corresponding to the total trajectory, where n is the data volume of the acquired data in a sub-segment.

4. The azimuth decimation method according to claim 1, characterized in that, when segmenting the working trajectory of the navigation satellite, ensure that when the imaging result obtained after segmentation is compared with the imaging result before segmentation, the amplitude error is less than 1%, and the phase error is less than 0.5 degrees.

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