Joint Angle-Doppler Estimation With Coprime Sampling On A Uniform Circular Array

This paper is addressed on the joint angle-doppler estimation (JADE) for the uniform circular array (UCA) with coprime sampling. Space-time adaptive processing (STAP) can conveniently estimate direction-of-arrival (DOA) and radial velocities of emitting sources. And UCA can realize the azimuth angle of the 360 detection without angle ambiguity. In this paper, we extend the coprime sampling for the linear array to UCA by utilizing the real beamspace transformation , we map the UCA manifold vector onto a virtual ULA manifold. And nonuniform time samples at different sensor of the virtual ULA can be employd to generate a full rank autocorrelation matrix by spatial smoothing. Then, we can use MUSIC algorithm to estimate the angle and doppler frequency jointly by applying UCA, coprime samples with STAP framework. Simulations show that making use of UCA also achieve good performance compared to coprime linear array. Introduction Space-time adaptive processing (STAP) is a normalized technique in airbone MTI radar signal processing [1]. It refers to the use of two-dimensional (2D) (direction-of-arrivals and Doppler frequencies) spatio temporal adaptive filters. There are many methods to estimate the angle-Doppler information, such as MUSIC algorithms [2], ESPRIT algorithms [3], time-space-time MUSIC [4], and so on. For coprime sampling [5], two uniform samplers with sample spacings as MT and NT are used, in which M and N are coprime and T is the minimum sampling interval. Coprime sampling can offer an enhanced degree of freedom. Uniform circular array (UCA) [6] is of interest in many applications, including radar, sonar and navigation. Because it has desirable properties, UCA is capable of providing 360 azimuthal coverage of the same aperture in any direction and also offers information for source elevation angles. However, uniform linear array (ULA) only in the −60 to 60 has a high angle resolution. So we propose the coprime sampling on UCA for estimating joint angle-Doppler [7] at the output of each sensor. Firstly, transforming the beamspace is to map the UCA to ULA; Secondly, taking advantage of spatial smooth is to construct autocorrelation matrix with full rank; Lastly, using MUSIC algorithm is to achieve JADE. By using UCA and coprime sampling, we proved that JADE also can be figured out and the performance is better. This paper is organized as follows. In Section 2, the signal model is briefly reviewed. In Section 3, real beamspace for uniform circular arrays is introduced in detail. In section 4, we propose beamforming and joint angle-doppler estimation, which are verified by simulations in section 5. The section 6 concludes the paper. 2nd Workshop on Advanced Research and Technology in Industry Applications (WARTIA 2016) © 2016. The authors Published by Atlantis Press 1011 Signal model Consider a UCA with M sensors in the space, there are D sources emitting electromagnectic wave impinging on the UCA. We take samples at time instant nT in time, T is the minimum sampling interval. At each sensor, two samplers run at sampling rates M1T and N1T, where M1 and N1 are coprime integers, n∈{0,M1, ··· (N1 −1) M1,N1, ··· (2M1 −1) N1}. Each source is represented by its DOA and its radial velocity with λ being the wave length [8]. The observation signal X(m,n) can be modeled as