Joint Space-Time Parameter Estimation for Underwater Communication Channels with Velocity Vector Sensor Arrays

In this paper, the problem of joint space-time parameter estimation for underwater wireless communication channels in a multipath environment is addressed. We consider the receive antenna array to be configured with multiple vector sensors, each of which consists of a pair of orthogonal velocity sensors. A quadrilinear model for the channel is formulated, and a quadrilinear decomposition method developed for joint angle and delay estimation (JADE). In addition, a computationally simple subspace-based algorithm is proposed for the problem under consideration. The basic idea behind this algorithm is to use the angle information embedded in the velocity vector sensors to start two polynomial rooting procedures for the angle and delay in succession. Simulation results are finally presented to verify the efficacy of the proposed algorithms.

I. Introduction

Joint space-time parameter estimation (i.e., joint angle and delay estimation (JADE)) is an important problem encountered in radar, sonar, and communications. It has applications also in source localization, position location and intelligent transportation [1]. Furthermore, since the propagation channels are usually characterized by multipaths in land-based radio and underwater acoustic wireless communication systems, with each multipath being parameterized by angle and delay, the channel estimation accuracy can be significantly improved by jointly exploring these angle and delay information [2], [3]. In the past decade, a variety of algorithms for JADE have been developed [4]–[12]. For example, the maximum likelihood (ML) algorithm and the subspace-based algorithms have been presented in [4] and [5]–[12], respectively. These algorithms fully exploit spatial diversity as well as temporal diversity to offer significant performance improvement over the traditional angle-based estimation algorithms.