@article{10902/33826,
year = {2024},
month = {2},
url = {https://hdl.handle.net/10902/33826},
abstract = {This paper addresses the passive detection of a common rank-one subspace signal received in two multi-sensor arrays. We consider the case of a one-antenna transmitter sending a common Gaussian signal, independent Gaussian noises with arbitrary spatial covariance, and known channel subspaces. The detector derived in this paper is a generalized likelihood ratio (GLR) test. For all but one of the unknown parameters, it is possible to find closed-form maximum likelihood (ML) estimator functions. We can further compress the likelihood to only an unknown vector whose ML estimate requires maximizing a product of ratios in quadratic forms, which is carried out using a trust-region algorithm. We propose two approximations of the GLR that do not require any numerical optimization: one based on a sample-based estimator of the unknown parameter whose ML estimate cannot be obtained in closed-form, and one derived under low-SNR conditions. Notably, all the detectors are scale-invariant, and the approximations are functions of beamformed data. However, they are not GLRTs for data that has been pre-processed with a beamformer, a point that is elaborated in the paper. These detectors outperform previously published correlation detectors on simulated data, in many cases quite significantly. Moreover, performance results quantify the performance gains over detectors that assume only the dimension of the subspace to be.},
organization = {The work of D. Ramírez was partially supported by MCIN/AEI/10.13039/501100011033/FEDER, UE, under grant PID2021-123182OB-I00 (EPiCENTER) and by the Office of Naval Research (ONR) Global under contract N62909-23-1-2002. The work of I. Santamaria was funded by MCIN/AEI/10.13039/501100011033, under Grant PID2022-137099NB-C43 (MADDIE). The work of L. L. Scharf was supported by the Office of Naval Research (ONR) under contract N00014-21-1-2145 and the Air Force Office of Scientific Research (AFOSR) under contract FA9550-21-1-0169. This paper was presented in part at the 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023).},
publisher = {Institute of Electrical and Electronics Engineers, Inc.},
publisher = {IEEE Transactions on Vehicular Technology, 2024, 73(7), 10106-10117},
title = {Passive detection of a random signal common to multi-sensor reference and surveillance arrays},
author = {Ramírez García, David and Santamaría Caballero, Luis Ignacio and Scharf, Louis L.},
}