Target Localization and Measurement Association in PCL-PET Hybrid Heterogeneous Network

This paper discusses the problem of target localization and measurement association in a hybrid heterogeneous network consisting of Passive Coherent Location (PCL) and Passive Emitter Tracking (PET). The distinction from existing literature lies in this paper's consideration of the general scen...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2024-10, p.1-15
Main Authors: Hu, Yueyang, Yi, Jianxin, Wan, Xianrong, Cheng, Feng
Format: Article
Language:English
Subjects:
Accuracy
Aerospace and electronic systems
Artificial neural networks
Frequency measurement
Heterogeneous networks
Location awareness
Measurement errors
Measurement uncertainty
Receivers
Target tracking
Online Access:Get full text
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Summary:This paper discusses the problem of target localization and measurement association in a hybrid heterogeneous network consisting of Passive Coherent Location (PCL) and Passive Emitter Tracking (PET). The distinction from existing literature lies in this paper's consideration of the general scenario where PCL receivers can only receive signals from specific transmitters. Two target localization algorithms are proposed based on semidefinite relaxation and Newton-Homotopy methods, corresponding to situations where the initial target position is unknown and known, respectively. Furthermore, this paper introduces a measurement association algorithm for the PCL-PET hybrid heterogeneous network. It demonstrates that the test statistic follows a chi-square distribution, providing theoretical guidance for selecting thresholds in hypothesis decisions. Monte Carlo simulations indicate that the proposed localization algorithms achieve accuracy close to the Cramér-Rao Lower Bound (CRLB), and the measurement association algorithm effectively discerns whether measurements originate from the same target. Additionally, contour plots of localization accuracy illustrate the more significant potential of the PCL-PET hybrid heterogeneous network compared to single PCL and PET networks.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2024.3486263