Adaptive beamformer

About: Adaptive beamformer is a research topic. Over the lifetime, 4934 publications have been published within this topic receiving 93100 citations.

Applications of minimum redundancy arrays in adaptive beamforming

Abstract: It is shown, through analysis and simulation, that the use of a minimum redundancy array (MRA) in conjunction with an adaptive beamformer results in performance superior to that attained by a comparable system based on an array with uniformly spaced elements, or uniform array (UA) in terms of rejecting interferences located in close angular proximity to the look direction. Further, it is demonstrated that choosing the adaptive elements of a thinned adaptive array (TAA) based on a minimum spatial redundancy criterion, rather than spacing them uniformly, results in improved rejection of main lobe interferences, with negligible degradation in sidelobe interference rejection capabilities.

ADS-B Signal Separation Based On Blind Adaptive Beamforming

Abstract: The automatic dependent surveillance-broadcast (ADS-B) is a surveillance system for air traffic management where aircrafts asynchronously broadcast the position and other information on the same frequency band. However, this simple transmission protocol will result in inevitable overlapping among multiple ADS-B signals. In this paper, with the inherent characteristics of the ADS-B signal, an algorithm is proposed to separate the overlapping ADS-B signals. First, a nonconvex blind adaptive beamforming problem is formulated where the constraints are different from those in common beamforming algorithms. Especially, for the non-overlapping snapshot, the relationship between the output of the beamformer and that of the first array element is constrained. After that, the alternating direction method of multipliers algorithm is utilized to solve the nonconvex blind adaptive beamforming problem. Simulations demonstrate that the proposed algorithm is effective even if there is only one non-overlapping snapshot.

Constrained beamforming for cyclostationary signals

Abstract: The classical linearly constrained minimum variance (LCMV) beamformer corresponds, in the general case, to the linear, time invariant (TI) and spatio-temporal (ST) complex filter, the output power of which is minimized under some linear constraints. Optimal for stationary signals, this beamformer becomes sub-optimal for (quasi)-cyclostationary observations for which the optimal complex filters are (poly)-periodic (PP) and, under some conditions of widely linear non-circularity. Using these results and the fact that PP filtering is equivalent to FREquency SHifted (FRESH) filtering, the purpose of this paper is to present a first extension of the classical LCMV beamformer, taking into account the potential (quasi)-cyclostationarity and non-circularity properties of the observations. This new cyclic LCMV beamformer is shown to have an equivalent cyclic generalized sidelobe canceller (GSLC) structure. The performance computation of this new cyclic beamformer shows the interest of the latter in cyclostationary contexts and opens a reflection about the optimal constraint choice.

Phased array radar cost reduction through the use of commercial RF systems on a chip

Abstract: Phased array radar systems have not yet made the cost and performance breakthrough needed for fielding in the large numbers required to support air traffic control or distributed weather radar. While there has been significant cost reduction in the aperture, the cost of the RF components for beamforming and signal distribution are still prohibitive. Emerging commercial RF Systems on a Chip (RFSoC) have the potential to address these cost challenges while at the same time providing the ability to implement real-time digital signal processing algorithms not possible just a few years ago. Under the DARPA Arrays at Commercial Timescales (ACT) program and through internal funding we demonstrated the use of a prototype RFSoC as a software defined receiver and waveform generator along with real-time adaptive beamforming in an S-band phased array radar. The focus of the research has been to demonstrate the potential improvement for size weight and power (SWaP), real-time signal processing capacity and advanced design processes for rapid algorithm implementation. The pre-production RFSoC prototype demonstrates the potential value of RFSoC and rapid algorithm development for next generation radar systems.

Low-Complexity Constrained Adaptive Reduced-Rank Beamforming Algorithms

Abstract: A reduced-rank framework with set-membership filtering (SMF) techniques is presented for adaptive beamforming problems encountered in radar systems. We develop and analyze stochastic gradient (SG) and recursive least squares (RLS)-type adaptive algorithms, which achieve an enhanced convergence and tracking performance with low computational cost, as compared with existing techniques. Simulations show that the proposed algorithms have a superior performance to prior methods, while the complexity is lower.