Real-Time Software Architecture for EM-Based Radar Signal Processing and Tracking

Alan Nussbaum, B. Keel, W. Blair, U. Ramachandran
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Abstract

While a radar tracks the kinematic state (position, velocity, and acceleration) of the target, an optimal signal processing requires knowledge of the target's range rate and radial acceleration that are derived from the tracking function in real time. High precision tracks are achieved through precise range and angle measurements whose precision are determined by the signal-to-noise ratio (SNR) of the received signal. The SNR is maximized by minimizing the matched filter loss due to uncertainties in the radial velocity and acceleration of the target. In this paper, the Expectation-Maximization (EM) algorithm is proposed as an iterative signal processing scheme for maximizing the SNR by executing enhanced range walk compensation i.e., correction for errors in the radial velocity and acceleration) in the real-time control loop software architecture. Maintaining a stringent timeline and adhering to latency requirements are essential for real-time sensor signal processing. This research aims to examine existing methods and explore new approaches and technologies to mitigate the harmful effects of range walk in tracking radar systems with an EM-Based iterative algorithm and implement the new control loop steering methods in a real-time computing environment.
基于电磁的雷达信号处理与跟踪实时软件体系结构
当雷达跟踪目标的运动状态(位置、速度和加速度)时,最优的信号处理需要了解目标的距离速率和径向加速度,这些都是由跟踪函数实时导出的。高精度跟踪是通过精确的距离和角度测量来实现的,其精度由接收信号的信噪比决定。通过最小化由于目标径向速度和加速度的不确定性而导致的匹配滤波器损失来实现信噪比的最大化。本文提出了期望最大化(EM)算法作为一种迭代信号处理方案,通过在实时控制环路软件架构中执行增强距离行走补偿(即校正径向速度和加速度误差)来最大化信噪比。保持严格的时间线和遵守延迟要求对于实时传感器信号处理至关重要。本研究旨在研究现有方法,探索新的方法和技术,以减轻跟踪雷达系统中基于em的迭代算法的距离行走的有害影响,并在实时计算环境中实现新的控制回路转向方法。
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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