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Target tracking using adaptive compressive sensing and processing

机译:使用自适应压缩感测和处理的目标跟踪

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摘要

Compressive sensing and processing (CSP) performs signal acquisition and processing at sub-Nyquist rates. This makes CSP an attractive option in radar target tracking as it reduces computational load in sequential signal acquisition and processing. However, CSP is accompanied by a reduction in signal to noise ratio (SNR) which results to a deterioration of tracking performance. In order to improve tracking performance CSP can be configured using information available on the target state which is provided by the sequential estimation process. In this work, adaptive CSP is applied to a target tracking scenario. A particle filtering implementation using adaptive CSP is developed for tracking a single target. Simulation results are provided to demonstrate the improvement in SNR and in tracking a single target by adaptive CSP over non-adaptive CSP and previously proposed adaptive CSP methods.
机译:压缩感测和处理(CSP)以次奈奎斯特速率执行信号采集和处理。这使得CSP在雷达目标跟踪中成为有吸引力的选择,因为它减少了顺序信号采集和处理中的计算负荷。但是,CSP伴随着信噪比(SNR)的降低,从而导致跟踪性能下降。为了提高跟踪性能,可以使用由顺序估计过程提供的有关目标状态的可用信息来配置CSP。在这项工作中,将自适应CSP应用于目标跟踪方案。开发了使用自适应CSP的粒子过滤实现方案来跟踪单个目标。提供了仿真结果,以证明与非自适应CSP和先前提出的自适应CSP方法相比,自适应CSP可以改善SNR并跟踪单个目标。

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