Generalised parametric Rao test for multi-channel adaptive detection of range-spread targets

Author(s): P. Wang ; H. Li ; T.R. Kavala ; B. Himed
DOI: 10.1049/iet-spr.2011.0313

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Author(s): P. Wang ¹ ; H. Li ¹ ; T.R. Kavala ¹ ; B. Himed ²
- Affiliations: 1: Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, USA
  2: Department of Electrical and Computer Engineering, AFRL/RYMD, Dayton, USA
Source: Volume 6, Issue 5, July 2012, p. 404 – 412
DOI: 10.1049/iet-spr.2011.0313 , Print ISSN 1751-9675, Online ISSN 1751-9683

This study considers the problem of detecting a multi-channel signal of range-spread targets in a homogeneous environment, where the disturbances in both test signal and training signals share the same covariance matrix. To this end, a generalised parametric Rao (GP-Rao) test is developed by modelling the disturbance as a multi-channel auto-regressive process. The GP-Rao test uses less training data and is computationally more efficient, when compared with conventional covariance matrix-based solutions. The theoretical detection performance of the GP-Rao test is characterised in terms of the asymptotic distribution under both hypotheses. Numerical results indicate that the proposed GP-Rao test attains asymptotically the constant false alarm rate property. Numerical results show that the GP-Rao test achieves better detection performance and uses significantly less training signals than the covariance matrix-based approach.

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Generalised parametric Rao test for multi-channel adaptive detection of range-spread targets

Generalised parametric Rao test for multi-channel adaptive detection of range-spread targets

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