Research On Passive Radar Detection Of Targets By Using Spaceborne Transmitters

Passive radar has incomparable advantages over conventional radars,and it is a kind of radar system with broad development prospects.However,due to the characteristics of the external source radar,its signal processing scale is large,which brings huge challenges to the traditional signal processing.First,for the detection of long-distance high-speed moving targets,the system needs to search for a large range of time delay and Doppler frequency.At the same time,in order to improve the signal-to-noise ratio of energy accumulation,the signal processing end needs to accumulate energy for a long time.Directly calculating the cross-ambiguity function to estimate the target time delay and Doppler frequency has a huge amount of calculation,which is difficult to meet the real-time requirements of the radar system.Secondly,the echo of the moving target received by the radar receiving station has the phenomenon of moving across the distance unit,which will cause accumulated gain loss,and ultimately lead to inaccurate target detection.Therefore,solving the moving problem of the target echo and making full use of the signal energy have become the key to the detection of moving targets.Finally,due to the limitation of the observation time and the requirements of the observation distance,the target echo is usually very weak and is covered by noise and clutter.The signal-to-noise ratio after the target energy accumulation is difficult to meet the requirements of traditional detection methods.Therefore,the research of target detection methods under low signal-to-noise ratio is also particularly important.The specific research content of this paper is as follows:1.A calculation method of cross-ambiguity function based on surface fitting is proposed.First,a model of the spaceborne radiator radar system is established to analyze the radiator signal.For the problem of cross-ambiguity function calculation,the calculation complexity of the direct calculation method,the one-dimensional parameters+FFT algorithm,and the piecewise coherent accumulation algorithm are analyzed.Then,in order to realize the rapid calculation of the cross-ambiguity function and the accurate extraction of the target peak value,a calculation method of the cross-ambiguity function based on surface fitting is proposed.This method can reduce the calculation amount of cross-ambiguity function to a certain extent,and can improve the estimation accuracy of time delay and Doppler frequency.Finally,the simulation data and the measured data received by Asia VII are used to carry out verification experiments.The method proposed in this paper is compared with the existing time-frequency difference parameter extraction method,and the performance of the proposed method is verified.2.Research on the compensation algorithm for cross-distance unit movement based on Keystone transform and the compensation algorithm for cross-distance unit movement based on Radon-Fourier transform.Due to the movement of the observation target,the target echo moves between the distance units.The movement of the target echo will cause the target energy to diffuse and lose the energy accumulation signal-to-noise ratio.Therefore,when energy is accumulated,it is necessary to use the cross-range unit walk compensation method to compensate for the movement to improve the energy accumulation signal-to-noise ratio.The compensation algorithm for cross-distance unit movement based on Keystone transform transforms the support domain through an interpolation algorithm,thereby eliminating the target's cross-distance unit movement.Based on Radon-Fourier transform,the compensation algorithm for the movement of the unit across the distance is to integrate the time delay line where the target is located by searching for the phase difference,so as to compensate the movement of the unit across the distance.Finally,the research method is verified by simulation experiment and the measured data received by Asia VII,and the performance of different compensation methods is compared and analyzed.3.A target detection method based on the maximum a posteriori probability(Maximum A Posteriori,MAP)of the passive radar is proposed.Because the satellite transmitter is far from the ground,the direct wave and target echo received by the radar are weak,and the signal-to-noise ratio after energy accumulation is difficult to reach the detection threshold of the traditional detection method.Therefore,the "spikeness" and non-Gaussianness of the target correlation peak can be used to transform the target detection problem into a feature extraction problem.The background clutter and the target are modeled separately,and combined with the prior information of the background clutter and target signal,the maximum likelihood estimation of the parameter set is obtained by iterative solution of the maximum posterior probability method,so as to realize the detection of the target.Finally,the method is tested on the measured data received by Asia ?,and the detection performance of the method is compared with the Constant False-Alarm Rate(CFAR)detection algorithm to verify the detection performance of the proposed method.