Clutter intensity divided self-adaptive dynamic target detection

Abstract

The invention relates to clutter intensity divided self-adaptive dynamic target detection. An M times echo data of pulse Doppler radar in a coherent processing interval is rearranged, the arranged data is divided into primary and secondary channels, wherein the auxiliary channel adopts an FFT (Fast Fourier Transform Algorithm) to process, and an auxiliary channel clutter map is established as the basis of the selection of the primary channel fir filter bank weight coefficient; the primary channel is realized by adopting the fir filter bank; and the number of the weight coefficients of each filter is 4 which respectively correspond to different ground clutter and weather clutter situations, and one of the four weight coefficients is selected as the fir filter weight coefficient of the primary channel according to the auxiliary channel clutter map. The self-adaptive dynamic target detection provided by the invention has the advantages that the primary and secondary channels are adopted to process, the auxiliary channel is processed by adopting FFT, and the primary channel is realized by adopting the fir filter bank; and the auxiliary channel clutter map is established to indicate the current clutter background of the radar, and the weight coefficient of the primary channel fir filter is selected according to the clutter intensity.

Description

technical field [0001] The invention belongs to the technical field of target detection in radar signal processing, and in particular relates to an adaptive moving target detection with clutter strength division. Background technique [0002] Object detection is an essential component of radar signal processing systems. The traditional moving target detection method of pulse Doppler radar mainly includes two methods such as weighted FFT and MTI+weighted FFT. The processing method has a small amount of calculation and is easy to implement. Using the weighted FFT algorithm, in order to obtain a larger ground clutter improvement factor, no matter it is in the clutter area or in the non-clutter area, it needs to be weighted. Most of them are realized by window function, and the signal-to-noise ratio generally has a loss of about 1.5dB. . As for the MTI+FFT method, although the multi-pulse cancellation method can better suppress the influence of ground clutter, it will cause di...

AI Technical Summary

Problems solved by technology

Using the weighted FFT algorithm, in order to obtain a larger ground clutter improvement factor, no matter it is in the clutter area or in the non-clutter area, it needs to be weighted. Most of them are realized by window function, and the signal-to-noise ratio generally has a loss of about 1.5dB.

For the MTI+FFT method, the multi-pulse cancellation method can suppress the influence of ground clutter, but it will cause differences in the responses of different velocity channels, which will affect the calculation of the true Doppler of the target.

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