Distributed radar incoherent fusion method for independent non-identically distributed fluctuating targets

In the research of distributed radar incoherent fusion, most of them consider independent identically distributed target RCS models, furthermore the signal-to-noise ratios of each node of the radar may differ greatly under non-ideal conditions, which reduces the detection performance of the incoherent detector. Therefore, this paper investigates the node selection of independently non-identically distributed lognormal fluctuating targets for incoherent detector under distributed radar. Specifically, this paper approximates the lognormal sum by using a new lognormal probability density function (pdf) and gives an approximate expression for the detection probability. Finally, some conclusions are drawn from numerical simulation experiments on node selection.

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Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/icsidp62679.2024.10868151
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
0.00

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Distributed radar incoherent fusion method for independent non-identically distributed fluctuating targets

Huageng Liu, Han Chen, Zihao Zhou, Yuanyuan Song et al.
Radar Systems and Signal Processing
article

Distributed radar incoherent fusion method for independent non-identically distributed fluctuating targets

Huageng Liu, Han Chen, Zihao Zhou, Yuanyuan Song, Zeyu Ping
article en

Abstract

In the research of distributed radar incoherent fusion, most of them consider independent identically distributed target RCS models, furthermore the signal-to-noise ratios of each node of the radar may differ greatly under non-ideal conditions, which reduces the detection performance of the incoherent detector. Therefore, this paper investigates the node selection of independently non-identically distributed lognormal fluctuating targets for incoherent detector under distributed radar. Specifically, this paper approximates the lognormal sum by using a new lognormal probability density function (pdf) and gives an approximate expression for the detection probability. Finally, some conclusions are drawn from numerical simulation experiments on node selection.

Beijing Institute of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 55%
Radar Systems and Signal Processing
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