Earticle

초록

영어

In this study, to accurately estimate targets in a maritime environment, the radar cross section (RCS) is modeled using a Weibull distribution, and likelihood maximization together with QR decomposition is applied to the RML algorithm to minimize the angle-of-arrival (AoA) error. In the simulation experiments conducted with a 64-element antenna array and a Signal-to-Noise Ratio (SNR) of 23 dB, the proposed algorithm demonstrated significant performance improvement compared to the conventional RML algorithm. Specifically, the estimation error rate for the Angle of Arrival (AOA) was reduced from 0.058 degrees (conventional RML) to 0.04 degrees (proposed method), which represents a 31% reduction in directional error. Furthermore, the proposed algorithm substantially reduced the velocity estimation error during the initial target extraction phase, showing an estimated reduction of approximately 4 m/s compared to the RML method. The simulation also clarified the experimental setup by conducting 1,000 Monte Carlo runs to ensure reproducibility. The results statistically validate that applying QR decomposition to RML offers superior performance in maritime target extraction by effectively removing surface-signal clutter.

목차

Abstract
1. Introduction
2. Sea Clutter Characteristics
3. Target Estimation Algorithm
4. Simulation
5. Conclusion
References

키워드

저자

• Kwan Hyeong Lee [ Professor, Division AI Convergence, Deajin University, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Internet, Broadcasting and Communication

• 간기

  계간

• pISSN

  2288-4920

• eISSN

  2288-4939

• 수록기간

  2009~2025

• 십진분류

  KDC 326 DDC 380