In this paper, we consider the problem of estimating the angularparameters, i.e., the nominal angle-of-arrivals (AoAs) and angular spreads, of incoherently distributed sources using the phased-array equipped with a s...
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In this paper, we consider the problem of estimating the angularparameters, i.e., the nominal angle-of-arrivals (AoAs) and angular spreads, of incoherently distributed sources using the phased-array equipped with a single RF chain. We first derive the approximate Fourier series of the received power. The coefficients can be expressed in closed form with the angularparameters. In the case of single source, this finding directly suggests the design of the low-complexity algorithm that performs spatial sampling and discrete Fourier transform to estimate the Fourier series coefficients, from which the nominal AoA and angular spread can be obtained successively. In the case of multiple sources, we focus on one source at one time, and the multiples sources are handled one by one. Based on the Fourier series expression, the power fitting approach is proposed to build the nonlinear least-squares problem. Then, the semi-exhaustive search algorithm is developed to find the solution, which gives the angularparameters of the target source. Additionally, the approximate Cramer-Rao bound is derived as benchmark. The numerical results demonstrate that in certain cases, the proposed methods can even outperform the existing method that uses fully-digital array.
This paper presents an effective angular parameter estimation method based on the manifold separation technique (MST) for incoherently distributed sources, named as MST-ID algorithm. In the proposed method, at first, ...
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This paper presents an effective angular parameter estimation method based on the manifold separation technique (MST) for incoherently distributed sources, named as MST-ID algorithm. In the proposed method, at first, a mathematical model is established through the first-order Taylor expansion of the steering vector, in which the nominal direction of arrival (DOA) can be decoupled from the angular spread. Then, the decoupled steering vector is divided into two sub-steering vectors with equal dimensions, and further the nominal DOA is estimated by the shift invariant structure between the sub-steering vectors. Finally, the MST is used to separate the antenna array structure from the nominal DOA in the array steering vector, such that the signal covariance matrix can be easily obtained according to the antenna array structure and the estimated nominal DOA. On this basis, a spectrum search function is given to estimate the angular spread. Compared with the previous works, the presented method can not only improve the angular parameter estimation accuracy but also be suitable for arbitrary line array structures. Theoretical analysis and simulation results confirm the effectiveness of the proposed method.
The distributed source parameter estimator (DSPE) is one of the well-known angular parameter estimation techniques for coherently distributed sources. However, the computational cost of DSPE is not attractive due to t...
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The distributed source parameter estimator (DSPE) is one of the well-known angular parameter estimation techniques for coherently distributed sources. However, the computational cost of DSPE is not attractive due to the two-dimensional spectrum peak search. To overcome this problem, this letter proposes a novel DSPE algorithm based on compressive sensing theory, named as LP-DSPE algorithm. In the proposed method, at first, the nominal direction of arrival (DOA) estimation can be transformed into a linear programming problem through sparse recovery theory, whose feasible solution set is further expanded to improve the estimation accuracy. Then the angular spread can be obtained via a one-dimensional peak search utilizing the estimated nominal DOA. Compared with the previous works, the proposed algorithm can offer more accurate parameterestimation performance with lower computational complexity, even if in large angular spread scenarios. Theoretical analysis and simulation results demonstrate the performance of the proposed approach.
In this paper, a low complexity ESPRIT algorithm for coherently distributed noncircular source is proposed. Due to the utilization of noncircular source, the proposed algorithm derives both the received signal and its...
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In this paper, a low complexity ESPRIT algorithm for coherently distributed noncircular source is proposed. Due to the utilization of noncircular source, the proposed algorithm derives both the received signal and its conjugate to obtain the extended received data matrix and covariance matrix. When compared to the conventional ESPRIT algorithm, the algorithm considering noncircular properties can provide more accurate estimation performance. Numerical simulation results verifies the validity and reliability of the proposed algorithm.
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