Çoklu Yansıma Ortamlarında Geniş Menzilli Hedeflerin Uyarlanabilir Radar Tespiti

Year 2023, , 2583 - 2593, 01.12.2023

Harun Taha Hayvaci

https://doi.org/10.21597/jist.1274648

Abstract

Bu makalede, Gauss gürültüsü altında gömülü geniş menzilli radar hedeflerinin uyumlu algılama problemi, dağınık çoklu yol ortamı varsayımı altında ele alınmıştır. Her aralık hücresinden hedef yankısı, doğrudan yol bileşenini hesaba katan bilinmeyen bir ölçek faktörüyle belirlenen belirli bir veri vektörü ve bir parlak yüzeyin çoklu yankılarını temsil eden bilinmeyen bir kovaryans matrisiyle Gaussian dağılımlı rastgele veri vektörünün toplamı olarak modellemiştir. Tasarım aşamasında, her birincil veri kovaryans matrisi, ikincil veri seti ile elde edilen örnek bir kovaryans matrisi çevresinde yer aldığı varsayılır. Adaptif tespit problemi için bir kısıttlı Genelleştirilmiş Olasılık Oranı Testi (GLRT) ele alınmıştır. Geliştirilen algoritmanın, literatürdeki iyi bilinen adaptif dedektörlerle performans analizi yapılmıştır. Sunulan sonuçlar ve performans analizi, önerilen yaklaşımın yayılmış çoklu yol varlığı olan ortamlarda geniş menzilli radar hedeflerinin tespit performansını artırdığını vurgulamaktadır.

Keywords

Adaptif Radar Tespiti, Çoklu Yol Kullanımı, Geniş Menzilli Hedefler, Kısıtlı Optimizasyon, Genelleştirilmiş Olasılık Oranı Testi

Adaptive Radar Detection of Extended Targets in Diffuse Multipath Environments

Abstract

This paper discusses the adaptive detection of extended radar targets buried in Gaussian clutter, assuming a diffuse multipath environment. The target return signal from each range cell is modeled as the sum of a deterministic data vector, which includes an unknown scaling factor representing the direct path component, and a randomly distributed data vector in a Gaussian distribution with unknown covariance matrix representing multipath echoes. During the design phase, it is assumed that the primary data covariance matrix falls within the vicinity of a sample covariance matrix that is devised from the secondary data set. The paper proposes a constraint Generalized Likelihood Ratio Test (GLRT) for the adaptive detection problem of extended radar targets in diffuse multipath environments, and conducts a performance analysis comparing the developed algorithm with well-known adaptive detectors in the literature. The results and performance analysis demonstrate that the proposed approach enhances the detection performance of extended radar targets in environments with diffuse multipath. Overall, this article provides valuable insights for improving the adaptive detection of extended targets in challenging environments, with potential applications in radar and sensing technologies.

Keywords

Adaptive Radar Detection, Multipath Exploitation, Range Extended Targets, Constrained Optimization, Generalized Likelihood Ratio Test

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