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Waveform Design for Multi-Target Detection Based on Two-Stage Information Criterion.

Yu Xiao^1,2, Xiaoxiang Hu¹

¹School of Automation, Northwestern Polytechnical University, Xi'an 710072, China.

Entropy (Basel, Switzerland)

|August 26, 2022

Summary

This summary is machine-generated.

This study introduces a novel two-stage waveform design for Multiple-Input Multiple-Output (MIMO) radar, enhancing target detection. The method improves parameter estimation accuracy and reduces the average sample number (ASN) for sequential hypothesis tests.

Keywords:

KLD MI information criterion multi-target detection waveform design

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Area of Science:

Radar Systems Engineering
Signal Processing
Information Theory

Background:

Parameter estimation accuracy and average sample number (ASN) reduction are critical for sequential hypothesis tests in target detection.
Multiple-Input Multiple-Output (MIMO) radar offers a way to balance these factors using waveform diversity.

Purpose of the Study:

To propose a waveform design method using a two-stage information criterion to enhance multi-target detection performance.
To improve parameter estimation accuracy and reduce ASN in MIMO radar systems.

Main Methods:

A two-stage waveform design approach is presented.
Stage 1: Maximizes mutual information (MI) for parameter estimation under signal-to-noise ratio (SNR) constraints.
Stage 2: Minimizes MI and maximizes Kullback-Leibler divergence (KLD) between multi-hypothesis posterior probabilities, selecting waveforms from Stage 1 library.

Main Results:

The proposed two-stage waveform design enables rapid target direction detection.
Dual-hypothesis MI minimization improves parameter estimation performance.
Dual-hypothesis KLD maximization enhances target detection performance.

Conclusions:

The developed waveform design method effectively improves multi-target detection in MIMO radar systems.
The two-stage information criterion provides a robust framework for adaptive waveform design.
This approach offers significant advantages in balancing estimation accuracy and detection efficiency.