Abstract
Sparse arrays can generate a larger aperture than traditional uniform linear arrays (ULA) and offer enhanced degrees-of-freedom (DOFs) which can be exploited in both beamforming and direction-of-arrival (DOA) estimation. One class of sparse arrays is the coprime array, composed of two uniform linear subarrays which yield an effective difference co-array with higher number of DOFs. In this work, we present a new coprime array structure termed thinned coprime array (TCA), which exploits the redundancy in the structure of the existing coprime array and achieves the same virtual aperture and DOFs as the conventional coprime array with much fewer number of sensors. An analysis of the DOFs provided by the new structure in comparison with other sparse arrays is provided and simulation results for DOA estimation using the compressive sensing based method are provided.
Highlights
Sparse arrays can detect more sources than the number of sensors due to increased number of degrees of freedom (DOFs) available from their difference co-array model [1, 2]
We propose a thinned coprime array (TCA), a new structure resulting from exploiting the redundancy in the difference co-array model of the conventional coprime array
Simulation results for the proposed thinned coprime array are compared with the nested array and the conventional coprime array through the compressive sensing (CS)-based DOA estimation method
Summary
Sparse arrays can detect more sources than the number of sensors due to increased number of degrees of freedom (DOFs) available from their difference co-array model [1, 2]. A modification to this coprime array structure was proposed in [11] by increasing the number of elements in one subarray from M sensors to 2M sensors This structure of 2M + N − 1 sensors termed as conventional coprime array resulted in a significant increase in consecutive lags by providing 2M N + 2M − 1 consecutive lags which can be exploited using subspace based DOA estimation methods such as MUSIC [11,12,13]. A second type of array was proposed by introducing displacement between the two subarrays, resulting in an array with a larger minimum inter-element spacing, larger aperture and higher number of unique lags This array was termed as coprime array with displaced subarrays (CADiS).
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