7.1 Introduction

The DOA-delay estimation is a classical problem encountered in radar, sonar, and geophysics. It also finds applications in source localization, accident reporting, cargo tracking, and intelligent transportation [1]. Furthermore, in a multiray wireless communication system, one can obtain a better channel estimate by jointly exploring the ray DOAs and the ray propagation delays, significantly improving the system performance [2, 3].

Some algorithms for joint estimation of the DOAs and the multiray propagation delays were suggested recently. For example, Swindlehurst et al. [4 6] proposed several computationally efficient algorithms for the estimation of the delays of a multiray channel, and solved the spatial signatures (or DOAs) as a least-square problem. Clark et al. [7] proposed a two-dimensional IQML algorithm that could be extended to jointly estimate the channel parameters. All of the algorithms proposed in [4 7] take advantage of the Vandermonde structure of the estimated channel pulse response in the frequency domain. However, if two or more rays have close time delays, then the data covariance matrix becomes ill-conditioned, and these algorithms may not work properly, even if these rays possess diverse DOAs. In addition, the IQML-based algorithms suffer from the initialization problems. Based on the knowledge of the transmitted signals, Bertaux et al. [8] developed a PML technique that uses the iterative Gauss-Newton procedure to estimate the spatial-temporal parameters of a multipath channel. However, as a consequence of the stacking of the observed data matrix into a high-dimensional vector, the PML technique...