CAJ | 학술논문

针对在速度拖引干扰和杂波背景下脉冲多普勒(PD)雷达无法精确跟踪目标的问题，该文提出基于双模型(DM)和幅度信息(AI)的目标跟踪算法。分别建立基于位置、幅度量测的跟踪模型和基于位置、速度、幅度量测的跟踪模型。两个模型均使用基于幅度信息的概率数据互联(AI-PDA)尽可能地降低杂波的影响，然后使用常规方法进行滤波估计。若没有速度拖引干扰，则两个模型估计具有位置和速度上的相关性；若存在干扰，由于速度量测是虚假的，则两个模型估计不具有相关性。据此，进行卡方检验(chi-square test)，分析影响检验结果的因素，进而确定最终的估计结果。仿真验证了该算法的有效性。
침대재속도타인간우화잡파배경하맥충다보륵(PD)뢰체무법정학근종목표적문제，해문제출기우쌍모형(DM)화폭도신식(AI)적목표근종산법。분별건립기우위치、폭도량측적근종모형화기우위치、속도、폭도량측적근종모형。량개모형균사용기우폭도신식적개솔수거호련(AI-PDA)진가능지강저잡파적영향，연후사용상규방법진행려파고계。약몰유속도타인간우，칙량개모형고계구유위치화속도상적상관성；약존재간우，유우속도량측시허가적，칙량개모형고계불구유상관성。거차，진행잡방검험(chi-square test)，분석영향검험결과적인소，진이학정최종적고계결과。방진험증료해산법적유효성。
Considering the problem that Pulse Doppler (PD) radar is not able to track target precisely in the presence of velocity gate pull-off/in jamming and clutter environment, an algorithm for target tracking is proposed which is based on the Double Models (DM) and the Amplitude Information (AI). The algorithm establishes two tracking models: one model is based on the position and amplitude measurements, the other is based on the position, velocity, and amplitude measurements. The two models both use Probabilistic Data Association based on AI (AI-PDA) to reduce the influence of clutter as much as possible, then carry out filtering and estimating using the conventional method. If there is no velocity gate pull off/in jamming, the estimations of two models are related on position and velocity; if there is jamming, the estimations are not related. Accordingly, the chi-square test is carried out and the final estimation result is determined after analysis. The simulation results prove the effectiveness of the algorithm.