Weak target detection method based on dynamic programming and fractional Fourier transform

Abstract

The invention provides a weak target detection method based on dynamic programming and fractional Fourier transform, which comprises the steps of firstly, quickly searching the most possible motion trail of a weak target, namely, the motion trail with the maximum echo energy, by using a dynamic programming algorithm; then extracting radar echoes of the motion trail with the maximum echo energy respectively, conducting fractional order Fourier transform on the track echoes to achieve phase compensation, and completing phase-coherent accumulation; and finally, setting a threshold in the fractional domain by using a CA-CFAR detection method to complete detection of the weak target. According to the invention, the signal is converted into the fractional domain through FrFT, phase-coherent accumulation of the signal is realized, and the accumulation gain is higher. Compared with an existing phase-coherent accumulation algorithm, a dynamic programming algorithm is used for searching a possible track of a target, traversal search is not needed, and the operation speed is higher. In conclusion, the method is higher in detection efficiency and accuracy in the aspect of weak target detectionin the radar.

Description

technical field [0001] The invention belongs to the technical field of radar detection, in particular to a weak target detection method based on Dynamic Programming (DP) and Fractional Fourier Transform (FrFT). Background technique [0002] In traditional radar information processing, each frame echo is detected, and on this basis, the detected targets are correlated and filtered to form the target track. However, for small targets such as drones and birds, the radar cross-sectional area (Radar cross-sectional area, RCS) is small, the target echo signal is weak, and the single-frame echo signal-to-noise ratio (SNR) ) is low, it is difficult to be detected. [0003] Therefore, in order to detect small targets, the target signal needs to be accumulated for a long time to achieve a detectable signal-to-noise ratio. At present, the commonly used weak target echo accumulation methods can be divided into two categories: non-coherent accumulation detection and coherent accumulati...

AI Technical Summary

Problems solved by technology

However, the accumulation gain of this kind of non-coherent accumulation algorithm is low, and there is also the problem that the detection threshold is difficult to determine

[0005] Coherent accumulation processing can theoretically obtain higher accumulation gain than non-coherent accumulation, but due to the complexity of phase compensation, its calculation load is generally larger

During the long-term accumulation process, the target often undergoes range migration and Doppler walking, and its echo will be broadened in both the range domain and the Doppler domain, resulting in a sharp drop in the gain of the traditional pulse Doppler method

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