Abstract
Abstract We consider the joint estimation of the direction-of-arrival (DOA) and parameters of wideband polynomial-phase signals (PPSs) in sensor array. Unlike concurrent methods that require multidimensional searches, the proposed method requires 1D searches for all the parameters of interest. In this way, we can efficiently estimate the considered parameters in applications where large antenna arrays, containing tens or hundreds of sensors, are used. As special cases, we consider in detail the estimation of the second- and third-order PPSs. The former are estimated using the high-order ambiguity function (HAF), while the latter are estimated using the cubic phase function (CPF), known to outperform the HAF in terms of both accuracy and signal-to-noise ratio (SNR) threshold. In both cases, the estimation of the highest order parameter reaches the Cramér-Rao lower bound (CRLB), while the DOA estimation is above the CRLB for around 1 dB (second-order PPS) and around 6 dB (third-order PPS).
Highlights
An important application of polynomial-phase signal (PPS) estimation is related to the underwater monitoring of vessels and marine fauna [1,2,3], where large hydrophone arrays, containing tens or hundreds of sensors, are a common tool [4,5,6]
We proposed an efficient method for the estimation of DOA and parameters of PPS impinging on a uniform linear array (ULA)
As opposed to concurrent methods, it significantly reduces the computational complexity without a significant loss in accuracy
Summary
An important application of polynomial-phase signal (PPS) estimation is related to the underwater monitoring of vessels and marine fauna [1,2,3], where large hydrophone arrays, containing tens or hundreds of sensors, are a common tool [4,5,6]. Gershman et al [9], consider the joint estimation of DOA and PPS parameters using a technique called the polynomial-phase beamformer. This approach is more efficient than the maximum likelihood (ML) technique, it still requires a search over a multidimensional parameter space. The second-order PPS estimator, referred to as the chirp beamformer, requires a search over a 3D parameter space.
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