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In this paper, we present a novel approach to the problem of estimating and tracking the direction-of-arrival (DOA) of signals with known waveforms and unknown gains impinging on symmetric sparse subarrays. Unlike the conventional methods, which estimate the DOA based on the spatial signature of the signal with known waveform, the proposed method partitions the whole least square (LS) problem into...
An accurate direction-of-arrival (DOA) estimation algorithm with sparse sensor array is proposed. By dividing the nonuniform linear sparse array (NLSA) into two uniform linear sparse arrays (ULSA), the subarray response vectors yield a property of rotational invariance in the estimation of rough DOA without ambiguity using the so-called generalized ESPRIT. According to the estimated rough DOA, the...
Signal direction-of-arrival (DOA) estimation using an L-shaped array of sensors configured by two uniform linear arrays (ULA) has been an active research topic in array signal processing. A simple but efficient DOA estimation method has recently been proposed by exploiting the L-shape array geometry and the cross-correlation information of sensor data. In this paper, the asymptotic variance of the...
This paper presents a new method of estimating the direction-of-arrival (DOA) for multiple signals using minimum redundancy linear sparse subarrays (MRLSS). The proposed method makes use of the array structure to obtain the extended correlation matrix that is constructed by Kronecker Steering Vectors (KSVs) of which each contains the ambiguous and unambiguous angle with a one-to-one relationship....
This paper addresses the problem of the direction-ofarrival (DOA) estimation using fewer receivers than sensors. Inspired by the Compressed Sensing (CS) theory developed in recent years, we present a new preprocessing scheme for a large array using a small size receiver. Unlike the traditional ℓ2 -norm-based algorithms by judicious selection of the preprocessing matrix, the proposed scheme uses a...
A number of 2-D DOA estimation techniques based on L-shaped array have received much attention. In general, these methods require division of the L-shaped array into two independent uniform linear array (ULA) to obtain the azimuth and elevation angles independently, and then use additional pair matching technique to achieve 2-D DOA estimation. Therefore, these methods have some drawbacks such as 1)...
This paper presents a new blind direction of arrival (DOA) estimation approach for closely-spaced sources. The new method first estimates the autoregressive (AR) coefficients via an initial DOA estimation and then uses the AR coefficients for the linear extrapolation of the correlation matrix to implement a fine DOA estimation. Both initial and fine DOA estimations are performed using the estimation...
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