Performance Degradation of DOA Estimation in Distributed Radar Networks Under Near-Field Influence

In striving for optimal performance in distributed radar networks tailored for short-range applications, conventional direction-of-arrival (DOA) estimation often proves inadequate. The presence of close-in targets introduces a mismatch in the radar echo model, challenging the validity of far-field (...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on radar systems 2024, Vol.2, p.1148-1159
Main Authors: Li, Yi, Xia, Weijie, Zhu, Lingzhi, Zhou, Jianjiang, Chu, Yongyan, Zhang, Wogong, Zhang, Jie
Format: Article
Language:English
Subjects:
Direction of arrival (DOA)
Direction-of-arrival estimation
distributed radar networks
maximum-likelihood
misspecified Cramér-Rao bound (MCRB)
near-field (NF)
Noise measurement
Radar imaging
Radar tracking
Signal to noise ratio
System analysis and design
Systems architecture
Target tracking
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In striving for optimal performance in distributed radar networks tailored for short-range applications, conventional direction-of-arrival (DOA) estimation often proves inadequate. The presence of close-in targets introduces a mismatch in the radar echo model, challenging the validity of far-field (FF) assumptions. To address this problem, we have developed a misspecified Cramér-Rao bound (MCRB) for DOA estimation in distributed radar networks influenced by near-field (NF) effects. The derivation aids in understanding potential performance degradations associated with the mean-squared error (mse) of a misspecified maximum-likelihood estimator. Through comprehensive analysis, we explore the interaction between the usual Cramér-Rao bound (CRB) and the MCRB. Moreover, we conduct a meticulous investigation into the relationship between these bounds, target parameters, and system architecture. Our examination significantly advances radar performance in practical scenarios, providing valuable insights to inform the design and configuration of distributed radar systems.
ISSN:2832-7357
2832-7357
DOI:10.1109/TRS.2024.3493037