Integrated Sensing and Communication Target Detection Framework and Waveform Design Method Based on Information Theory

Integrated Sensing and Communication Target Detection Framework and Waveform Design Method Based on Information Theory

Target detection is a core function of integrated sensing and communication (ISAC) systems. The traditional likelihood ratio test (LRT) target detection algorithm performs inadequately under low signal-to-noise ratio (SNR) conditions, and the performance of mainstream orthogonal frequency division m...

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Bibliographic Details
Main Authors: Qilong Miao, Xiaofeng Shen, Chenfei Xie, Yong Gao, Lu Chen
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Sensors
Subjects:
target detection
integrated sensing and communication
information theory
OTFS
waveform design
Online Access:https://www.mdpi.com/1424-8220/25/2/465
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Summary:Target detection is a core function of integrated sensing and communication (ISAC) systems. The traditional likelihood ratio test (LRT) target detection algorithm performs inadequately under low signal-to-noise ratio (SNR) conditions, and the performance of mainstream orthogonal frequency division multiplexing (OFDM) waveforms declines sharply in high-speed scenarios. To address these issues, an information-theory-based orthogonal time frequency space (OTFS)-ISAC target detection processing framework is proposed. This framework adopts the OTFS waveform as its fundamental signal. The target detection is implemented through a relative entropy test (RET) comparing echo signals against target presence/absence hypotheses. Furthermore, to enhance the system’s target detection capability, the iterative OTFS-ISAC waveform design (I-OTFS-WD) method which maximizes the relative entropy is proposed. This method utilizes the minorization-maximization (MM) algorithm framework and semidefinite relaxation (SDR) technique to transform the non-convex optimization problem into an iterative convex optimization problem for resolution. The simulation results demonstrate that, under sufficient sample conditions, the RET algorithm achieves a 9.12-fold performance improvement over LRT in low-SNR scenarios; additionally, the optimized waveform reduces the sample requirements of the RET algorithm by 40%, further enhancing the target detection capability of the OTFS-ISAC system.
ISSN:1424-8220

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