Estimation Method of pri Agile Radar Target Parameters Based on Capon Algorithm

Abstract

The invention belongs to the technical field of radar signal processing, and specifically discloses a PRI agile radar target parameter estimation method based on a capon algorithm, comprising steps: the PRI agile radar transmits a signal and receives an echo signal; The transmitting carrier frequency is subjected to frequency mixing processing and pulse compression processing in turn to obtain the pulse-compressed echo signal; a filter corresponding to the capon algorithm is designed so that the pulse-compressed echo signal including the carrier frequency component of the input filter completely passes through, And the average output power of the filter is the minimum, and the minimum average output power is used as the capon power spectrum estimation of the echo signal; the distance and speed information of each target is determined. The invention can minimize the side lobe of the frequency characteristic by designing the filter, thereby obtaining accurate spectrum estimation results, and can accurately estimate the target parameters under the condition of low signal-to-noise ratio, with less calculation amount and fast operation speed.

Description

technical field [0001] The invention relates to the technical field of radar signal processing, in particular to a PRI agile radar target parameter estimation method based on a capon algorithm, which can be used in electronic reconnaissance, countermeasures, missiles and other fields. Background technique [0002] The pulse repetition period of the PRI agile radar signal changes rapidly within a certain range, and each repetition frequency can change according to a certain rule or randomly jump, and the jitter range is usually 1%-10%; the PRI agile radar has a series of advantages : 1) Since the PRI of the radar is an important parameter for signal sorting and identification, the agility of the PRI will increase the difficulty of signal sorting and identification, effectively improve the performance of anti-spoofing jamming, and have stronger low interception performance, 2) increase the radar Detection distance, 3) effectively suppress the interference of sea clutter and ot...

AI Technical Summary

Problems solved by technology

[0003] Due to the agility of the radar repetition frequency within a certain range, the sampling between different pulses on the same range unit has non-uniformity, and the traditional FFT technology cannot be directly used for coherent accumulation, which affects the high-resolution range image synthesis and Doppler information extraction of the target. The noise ratio is reduced and the reliability is not strong

There are several problems in the existing parameter estimation methods: 1) In multi-target scenarios, the side lobes interfere with each other and superimpose, which affects the performance of target motion parameter estimation; 2) The compressed sensing algorithm (CS) is used to sparsely reconstruct the echo signal , although it can effectively reduce sidelobes and has strong detection performance, but because it needs to build a perception matrix, increase complex operations, and is easily limited by sparsity, the accuracy of multi-target estimation is greatly reduced; 3) MUSIC algorithm is used for Spectrum estimation requires model-order prior knowledge, which obviously cannot meet the increasingly complex and changeable requirements of modern electronic warfare; 4) In a noisy environment, the target is easily submerged, and parameters cannot be accurately estimated

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