本文对基于压缩感知的压缩域目标跟踪算法进行了研究，为满足特定的应用场合要求，针对原算法的不足进行了改进，同时基于小型化低成本目标位置探测器设计思想及需求，设计并实现了以TMS320DM6437数字信号处理器为核心的实时图像跟踪处理平台，对算法在该DSP平台进行了实现与优化。仿真和实验结果表明，经过结合卡尔曼滤波器、融合LBP特征以及添加自适应学习速率更新策略等措施，算法的鲁棒性得到提高；对算法在DSP中的实现，经过一系列优化措施，对分辨率为960×960的视频图像，当取目标窗口为80×80时，处理速度可达25 f/s，能够满足实时性跟踪要求。系统能够对选定的运动目标进行连续、稳定地跟踪，能够满足特定应用场合下的目标位置探测与跟踪需求，具有一定的实用性，同时也对该类目标跟踪方法在嵌入式平台的研究与应用具有一定的参考价值。

The target tracking algorithm in compression domain based on compression perception is studied. To meet the specific application requirements, the shortcomings of original algorithm are improved. At the same time, based on the design idea and demand of miniaturized target position detector, a real-time image pro-cessing platform with TMS320DM6437 digital signal processor as the core is designed and implemented, and the algorithm is implemented and optimized on the DSP platform. The simulation and experiment results show that after the combination of Kalman filter, LBP feature and adding adaptive learning rate update strategy, the stability of the algorithm is improved. For the implementation in DSP, after a series of optimizing measures, as for an image with resolution of 960×960, taking the target window of 80×80 into account, the computation speed can be up to 25 fps, which can meet the requirement of real-time tracking. The embedded tracking system can track the selected moving objects continuously and stably, and can meet the target localization and tracking require-ments under specific applications, which has a real practical value. Moreover, the method in this paper has a certain reference value for the research and applications of this kind of target tracking method in the embedded platform.