采用模糊推理自適應(yīng)加權(quán)融合的雙色紅外成像目標(biāo)跟蹤
Target Tracking in the Dual Band IR Imaging System Using Adaptive Weighting Fusion Based on Fuzzy Inference
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摘要: 針對(duì)雙色紅外成像制導(dǎo)系統(tǒng)中多傳感器目標(biāo)跟蹤的實(shí)際問(wèn)題，提出了一種基于模糊推理自適應(yīng)加權(quán)融合的目標(biāo)跟蹤算法。該算法首先采用BP神經(jīng)網(wǎng)絡(luò)與模糊推理相結(jié)合的方法對(duì)各傳感器的工作性能進(jìn)行判決；然后根據(jù)各傳感器的性能測(cè)度對(duì)多傳感器測(cè)量數(shù)據(jù)進(jìn)行自適應(yīng)加權(quán)融合，得到目標(biāo)狀態(tài)的多傳感器重建測(cè)量；最后采用卡爾曼濾波器對(duì)多傳感器重建測(cè)量進(jìn)行濾波得到目標(biāo)狀態(tài)的最終估計(jì)。實(shí)驗(yàn)結(jié)果證明了該算法的有效性和穩(wěn)健性。
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關(guān)鍵詞:
- 目標(biāo)跟蹤;雙色紅外;模糊推理;信息融合
Abstract: Aim at the problem of multi-sensors target tracking in the dual band IR imaging system, a method of target tracking is presented using adaptive weighting fusion based on fuzzy inference. The algorithm firstly decides the performance of all sensors using a method integrated the BP neural network and fuzzy inference; Then, sums multi-sensors observation data adaptively with different weights based on the measure of these sensors to get the multi-sensors reconstruction observation of target position; Finally, filters the multi-sensors reconstruction observation using the Kalman filter to get the system estimate of target position. The result of experiments proved the effectiveness and robustness of the algorithm. -
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