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Research Article | Open Access | Online First

Joint Node Selection and Power Allocation for Phased Array Radar Network in Maneuvering Multi-Target Tracking under Non-Ideal Detection

Ting Cheng( ), Quan Zhou, Congchong Cao
School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
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Abstract

This paper addresses the problem of joint node selection and power allocation for phased array radar network in maneuvering multi-target tracking under non-ideal detection. Based on the objective of minimizing the total transmission power of all radar nodes while satisfying the target tracking accuracy thresholds and the given system resource constraints, a joint optimization problem model under non-ideal detection condition is established. A closed-form analytical expression for the predicted conditional Cramér–Rao lower bound (PC-CRLB) is derived, which is used as a measure of multi-target tracking accuracy under non-ideal detection. To tackle the nonlinear and non-convex optimization problem, a cyclic iterative framework based on a relaxed interior point method and a heuristic signal-to-noise ratio (SNR)-based initial point selection algorithm is adopted, and a joint node selection and power allocation under non-ideal detection (JNSPA-NID) scheme is proposed. Simulation results indicate that the proposed algorithm effectively reduces the total transmission power of the system while meeting the specified multi-target tracking accuracy requirements under non-ideal detection conditions compared to other comparative algorithms.

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Tsinghua Science and Technology

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Cite this article:
Cheng T, Zhou Q, Cao C. Joint Node Selection and Power Allocation for Phased Array Radar Network in Maneuvering Multi-Target Tracking under Non-Ideal Detection. Tsinghua Science and Technology, 2026, https://doi.org/10.26599/TST.2025.9010093

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Received: 30 November 2024
Revised: 02 April 2025
Accepted: 28 May 2025
Published: 29 September 2026
© The author(s) 2026.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).