DOA Estimation for Multi-Band Signal Sources Using Compressed Sensing Techniques with Khatri-Rao Processing

Abstract

SUMMARYMuch attention has recently been paid to direction of arrival (DOA) estimation using compressed sensing (CS) techniques, which are sparse signal reconstruction methods. In our previous study, we developed a method for estimating the DOAs of multi-band signals that uses CS processing and that is based on the assumption that incident signals have the same complex amplitudes in all the bands. That method has a higher probability of correct estimation than a single-band DOA estimation method using CS. In this paper, we propose novel DOA estimation methods for multi-band signals with frequency characteristics using the Khatri-Rao product. First, we formulate a method that can estimate DOAs of multiband signals whose phases alone have frequency dependence. Second, we extend the scheme in such a way that we can estimate DOAs of multi-band signals whose amplitudes and phases both depend on frequency. Finally, we evaluate the performance of the proposed methods through computer simulations and reveal the improvement in estimation performance.

Compressed sensing based low complexity 2D-DOA estimation by separation and pair-matching approach

“…On the other hand, the array input along the X-axis is also IEICE Communications Express, Vol. , [1][2][3][4][5][6] given by,…”

“…Since the computation for matrix inversion of H is the most dominant in HQR, its complexity is compared. Suppose the complexity order of Gaussian elimination based matrix inversion, straightforward 2D-DOA estimation requires O((L θ × L ϕ ) 3 ) whereas the proposed method can reduce it to O((L θ + L ϕ ) 3 ). These operations must be repeated until the convergence condition is satisfied.…”

“…Its notable feature is that one snapshot is sufficient. When the arrival waves are multi-band signals, the estimation accuracy can be improved more than the case of the single-band signals [3]. Further, it is known to possible to estimate the number of incident waves exceeding the physical degree of freedom of the antenna array.…”

Variable step‐size matching pursuit based on oblique projection for compressed sensing

“…Note that the problem of l 0 ‐minimisation is non‐deterministic polynomial‐hard and l 0 ‐norm in (4) can be transformed into l 1 ‐norm. The signal reconstruction can be solved as the following problem: The problem in (5) is convex, and the available methods are convex optimisation algorithms [28, 29], such as the BP algorithm. However, the conditions that guarantee l 0 ‐minimisation and l 1 ‐minimisation are not always satisfied [30].…”

Nested Circular Array and Its Concentric Extension for Underdetermined Direction of Arrival Estimation

“…To find the virtual elements and extend the array aperture, the KR subspace approach [11], [24] is applied. By using this approach, we can extend the DOFs of the NSCA and be able to perform underdetermined DOA estimation.…”