Translation Compensation and Resolution of Multi-ballistic Targets in Midcourse
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摘要: 彈道微動群目標時頻圖是多目標多散射點微多普勒的疊加，以往針對單目標的補償與分離方法不再適用。針對這一問題，該文首先分析了群目標及誘餌的微多普勒形式；利用彈道中段目標運動平穩(wěn)，短時觀測加速度近似為常數(shù)的特性，采用Radon變換檢測微多普勒曲線的傾斜程度，用最小熵準則和高斯函數(shù)擬合的方法估計平動參數(shù)，進而完成平動補償；對補償后的群目標時頻圖利用Viterbi算法提取各條微多普勒曲線，依據(jù)同一目標各散射點微多普勒的周期相關性，完成群目標分離；最后仿真驗證了以上方法的有效性。Abstract: Time-frequency image of multi-ballistic targets is composed of micro-Doppler of multi-targets with multi-scattering centers, which makes the methods for single target invalid. Firstly, micro-Doppler of precessing missile and swinging decoy is analyzed. Considering midcourse ballistic targets characteristics that the motion is stable and the acceleration is approximately a constant in short time, Radon transform is applied to the detection of linear degree of the micro-Doppler, then motional parameters are estimated based on minimum entropy criteria and Gauss fitting. After compensating translation, Viterbi algorithm is used to extract micro-Doppler from the time-frequency image, with which multi-targets can be resolved according to the principle that scattering centers on one target are with the same micro-Doppler cycles, but those on different targets are not. Finally, Simulations verify the effectiveness of the proposed method.
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