Modified linear predictive coding approach for moving target tracking by Doppler radar

Abstract

.Doppler radar is a cost-effective tool for moving target tracking, which can support a large range of civilian and military applications. A modified linear predictive coding (LPC) approach is proposed to increase the target localization accuracy of the Doppler radar. Based on the time-frequency analysis of the received echo, the proposed approach first real-time estimates the noise statistical parameters and constructs an adaptive filter to intelligently suppress the noise interference. Then, a linear predictive model is applied to extend the available data, which can help improve the resolution of the target localization result. Compared with the traditional LPC method, which empirically decides the extension data length, the proposed approach develops an error array to evaluate the prediction accuracy and thus, adjust the optimum extension data length intelligently. Finally, the prediction error array is superimposed with the predictor output to correct the prediction error. A series of experiments are conducted to illustrate the validity and performance of the proposed techniques.

A Target Localization Algorithm for a Single-Frequency Doppler Radar Based on an Improved Subtractive Average Optimizer

“…The accurate tracking and localization of human targets are essential in a wide range of civil and military applications [1][2][3][4]. Due to the outstanding advantages of penetrating ability, high measuring precision, and being scarcely influenced by light and weather conditions, Doppler radars play an increasingly important role in human target localization, such as in anti-terrorism detection [5,6], post-disaster rescue [7], military operations [8], indoor guidance [9], non-contact home monitoring [10], and so on. However, with the advancement of technology, there is an increasing demand for portable, cost-effective, and high-precision detection equipment for emergency applications.…”