Abstract
This paper addresses the problem of DOA estimation using uniform linear array (ULA) antenna configurations. We propose a new low-cost method of multiple DOA estimation from very short data snapshots. The new estimator is based on the annihilating filter (AF) technique. It is non-data-aided (NDA) and does not impinge therefore on the whole throughput of the system. The noise components are assumed temporally and spatially white across the receiving antenna elements. The transmitted signals are also temporally and spatially white across the transmitting sources. The new method is compared in performance to the Cramér-Rao lower bound (CRLB), the root-MUSIC algorithm, the deterministic maximum likelihood estimator and another Bayesian method developed precisely for the single snapshot case. Simulations show that the new estimator performs well over a wide SNR range. Prominently, the main advantage of the new AF-based method is that it succeeds in accurately estimating the DOAs from short data snapshots and even from a single snapshot outperforming by far the state-of-the-art techniques both in DOA estimation accuracy and computational cost.
Highlights
In recent years, there has been a surge of interest in array signal processing applications in both military and civil domains [1, 2]
We develop in this paper a new covariance-based direction of arrival (DOA) estimation method for uniform linear array (ULA) configurations which succeeds in estimating the DOA from very short data records
6 Conclusions In this paper, we derived a new DOA estimation method for multiple planar waves impinging on a ULA antenna array
Summary
There has been a surge of interest in array signal processing applications in both military and civil domains [1, 2]. It was used to successfully develop the so-called finite-rate-of-innovation (FRI) sampling method [9] where it led to signal sampling and reconstruction paradigms at the minimal possible rate (far below the traditional Nyquist rate) In this contribution, we apply for the first time the AF approach to DOA estimation for ULA configurations and, we will refer to our new technique as the AF-based method. The second one, referred to as “version II”, exploits the Toepltiz structure of the covariance matrix in order to enhance the estimation performance at low SNR levels In both versions, the obtained DOA estimates are used to find the unknown sources’ powers along with the noise variance.
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