Object Classification using Micro-Doppler Signature and Clutter Suppression in MIMO Radar

2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2022-07-08 DOI:10.1109/CONECCT55679.2022.9865108

Titas Ghoshal, K. Hari

引用次数: 1

Abstract

Radar(Radio-Detection and Ranging) has become very popular for several applications-in meteorology, defence, aircraft system and navigation system. The main purpose of the radar is to detect any object-moving or stationary. However, to get the micro-motion(internal motions of an object), we need to get micro-Doppler feature. In this report, the micro-Doppler feature of birds have been discussed using MIMO radar system as combination of several bistatic radar system. Also classification of multiple birds has been discussed in presence of noise and without noise. Also, adaptive signal processing technique (LMS,RLS,NLMS) has been discussed for clutter suppression . Finally application of LMS-Newton method has been discussed for clutter suppression.It can be seen that it has faster convergence compared to other algorithms.

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基于微多普勒特征和杂波抑制的MIMO雷达目标分类

雷达(无线电探测和测距)在气象、国防、飞机系统和导航系统等方面的应用已经非常普遍。雷达的主要目的是探测任何移动或静止的物体。然而，为了获得微运动(物体的内部运动)，我们需要获得微多普勒特征。本文讨论了多址多普勒雷达系统对鸟类微多普勒特征的影响。此外，还讨论了有噪声和无噪声情况下多种鸟类的分类。此外，还讨论了自适应信号处理技术(LMS、RLS、NLMS)对杂波的抑制。最后讨论了lms -牛顿法在杂波抑制中的应用。可以看出，与其他算法相比，它具有更快的收敛速度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)

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