The Applications And Researches Of Knowledge-aided Tbd Algorithm On The Airborne Radar

With the rapid development of the modern science and technology, the technologyof radar target detection is facing tough challenges. Because of the threat of low andsuper low altitude penetrative weapons and invisible targets, and the requirement ofdistant early warning, it is urgent to improve the performance of the airbornehigh-repetition early-warning radar on detecting and tracking faint target in strongclutter background.Addressing the issue of detecting and tracking the faint target by airbornehigh-repetition radar, this paper focuses on the research of the track-before-detectalgorithm based on DPA, and the faint target detection in strong clutter background andthe solution of distance ambiguity problem under high-repetition condition.This paper includes:1. According to the movement and measure models under high-repetition, thispaper analyses high-repetition track-before-detect algorithm based on dynamicprogramming and its performance when energy is accumulated.2. In regard to the issue of faint target detection in strong clutter background, thispaper first uses STAP algorithm to depress the clutter wave, then detecting the targetwith dynamic programming, and meanwhile analysing the effect that environmentalcategorical information has on the algorithm.3. In regard to the issue of faint target detection in strong clutter background, thispaper proposes a method based on the Doppler information of the target. This methoddepresses the clutter wave by ambiguity function and then starts the accumulationdetection using the high-repetition dynamic programming algorithm.4. In regard to the fuzzy distance issue of the path in the condition ofhigh-repetition, this paper analyses the traditional algorithm of the solutions of fuzzydistance and proposes an improved method based on single PRF solutions of fuzzydistance, which effectively solves the fuzzy distance issue of the path.