传感器选择:与其他选择方案比较,采用改进的riccati方程法

U. Ramdaras, F. Absil
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引用次数: 8

摘要

本文将基于改进Riccati方程(MRE)的传感器选择算法(SSA)与随机传感器选择(RSS)或固定传感器选择(FSS)方案进行了比较。目的是研究与其他选择方案相比,MRE SSA的收益。MRE SSA能够处理探测概率pd < 1的传感器,并根据目标跟踪场景中的各种预期性能标准进行传感器选择。对于所有三种选择方案,粒子滤波技术已用于目标跟踪,并在pd < 1的情况下自适应遗漏检测。对单个运动目标和两台静止雷达的模拟数据进行了多次运行比较。一个传感器输出距离、多普勒和方位信息,另一个传感器输出距离和方位信息。分析包括状态估计的质量和传感器的选择策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sensor selection: the modified riccati equation approach compared with other selection schemes
In this paper a comparison is made between a sensor selection algorithm (SSA) based on the modified Riccati equation (MRE) on the one hand, and a random sensor selection (RSS) or a fixed sensor selection (FSS) scheme on the other hand. The goal is to investigate the benefits the MRE SSA yields compared to the other selection schemes. The MRE SSA is capable of handling sensors with probability of detection pd < 1 and performs sensor selection based on various expected performance criteria in a target tracking scenario. For all three selection schemes the particle filtering technique has been used for target tracking with an adaption for missed detections in the case of pd < 1. Results are compared using multiple runs with simulated data for a single, moving target and two stationary radars. One sensor yields range, Doppler and bearing information, the other range and bearing information. The analysis includes the quality of the state estimate and the sensor selection strategy.
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