Adaptive Radar Detection Without Secondary Data for Uncooperative Spectrum Sharing Scenarios

被引：3

作者：

Coluccia, Angelo ^{[1
]}

Ricci, Giuseppe ^{[1
]}

Richmond, Christ D. ^{[2
]}

机构：

[1] Univ Salento, Dipartimento Ingegneria Innovazione, I-73100 Lecce, Italy

[2] Arizona State Univ, Sch Elect Comp & Energy Engn, Tempe, AZ 85287 USA

来源：

IEEE TRANSACTIONS ON SIGNAL PROCESSING | 2021年 / 69卷

关键词：

Radar; Training data; Radar detection; Detectors; Data models; Clutter; Covariance matrices; radar; communication coexistence; generalized likelihood ratio test; autoregressive models; POINT-LIKE TARGETS; HOMOGENEOUS CLUTTER; PARAMETRIC GLRT; SIGNAL; ALGORITHM; FILTER;

D O I：

10.1109/TSP.2021.3082472

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We address the design of GLRT-based, space-time radar detectors in presence of a communication signal. We consider a disturbance that is either spatially correlated and temporally white or spatially and temporally correlated. The former case assumes that the disturbance is modeled in terms of a scalar autoregressive filter while the latter case exploits a vector autoregressive filter. The filter parameters are unknown while the order is a design parameter. Finally, the direction of arrival of the communication signal is known. The analysis, conducted in comparison to natural competitors, also under mismatched conditions, shows the potential of the proposed approach.

引用

页码：3206 / 3219

页数：14

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