Work

Performance Research on Multi-Target Detection in Different Noisy Environments

Year: 2024

Type: article

Abstract: This paper studies five classic multi-target detection methods in different noisy environments, including Akaike information criterion, ration criterion, Rissanen's minimum description length, Gerschgorin disk estimator and Eigen-increment threshold methods. Theoretical and statistical analyses of these methods have been done through simulations and a real-world water tank experiment. It is known that these detection approaches suffer from array errors and environmental noises. A new diagonal correction algorithm has been proposed to address the issue of degraded detection performance in practical systems due to array errors and environmental noises. This algorithm not only improves the detection performance of these multi-target detection methods in low signal-to-noise ratios (SNR), but also enhances the robust property in high SNR scenarios.

Source: ADCAIJ ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL

DOI: 10.14201/adcaij.31710

Authors: Yuhong Yin, Qian Jia, Huiqi Xu, Guanglei Fu

Institutions: Xi'an Aeronautical University, Xi'an University of Finance and Economics, Northwestern Polytechnical University

Language: English

Topic: Direction-of-Arrival Estimation Techniques

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4404859196

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