Estimation Of Radar Target Parameters Based On Sparse Representation

In radar signal processing,radar target parameter estimation is one of the important task of radar target detection.For Traditional Doppler frequency estimation,radar resolution is determined by the coherent integration time,longer coherent accumulation time can get a higher resolution,but is limited by the radar system operating mode,the target's own characteristics and electromagnetic propagation environment,etc.Coherent accumulation time is limited.Therefore,when the high-precision estimation of the Doppler frequency of the target signal is quickly obtained under the limited coherent accumulation time,the classical method encounters a bottleneck.The appearance of sparse representation theory brings a new dawn to solve this problem.This paper mainly studies the application of sparse representation theory in radar target parameter estimation.Due to the same principle,this paper mainly studies Doppler frequency estimation as an example.Firstly,the basic theory of signal sparse representation is introduced.Secondly,a sparse model of signal Doppler frequency estimation is established,and a classical greedy iterative reconstruction algorithm is used to estimate the frequency,then a higher resolution is obtained;Based on the foregoing researc,aiming at the multi-path effect of Skywave Over-The-Horizon Radar,a sea clutter first-order peak matching algorithm based on sparse representation was proposed,which improved the detection performance of sea-ship target by Skywave Over-The-Horizon Radar.In this paper,radar signals are usually sparse in the Doppler frequency domain.Based on the prior information of the system,sparse modeling of the observation target scene is performed under the short coherent accumulation time.On the basis of the system modeling,the target echo is obtained.The signal model was deduced.For the known echo model with sparse prior information,this paper uses the orthogonal matching pursuit algorithm and regularized orthogonal matching pursuit algorithm with reduced number of iterations to estimate the Doppler frequency of the target,and it can be obtained that the accuracy is higher than the traditional Fourier analysis method through simulation experiments.For the unknown echo model with sparse prior information,the sparse adaptive matching pursuit algorithm is used to estimate the Doppler frequency of the target.Gradually,the algorithm adjusts the sparsity of the signal by adaptively adjusting the iteration step size to make an estimate.Under the condition of short coherent accumulation,the shielding problem of sea clutter in the Skywave Over-The-Horizon Radar target detection is mainly solved by the sea clutter cycle cancellation and high-resolution spectrum estimation method.In this paper,the sea clutter cycle cancellation is realized by using Root method,FFT phase analysis method and CAPES method respectively,and the sea clutter suppression is realized.When the radar echo sign al undergoes multipath effect in the ionosphere,multiple pairs of Bragg peaks appear in the Doppler spectrum in a distance unit.The conventional sea clutter cycle cancellation and high-resolution spectral estimation methods cannot separate the target and Multiple sea clutter's first-order spectral peaks.In order to solve this problems,a sparse representation based on first-order peak of sea clutter matching algorithm is studied.The method uses the characteristics of the constant difference of the positive and negative first-order peak Doppler frequency in the same propagation mode for sea clutter.The spectral peak pairing distinguishes the ship target and the first-order spectral peaks of the sea clutter to achieve the detection of ship targets.The effectiveness of the algorithm is verified by experimental simulations.