Adaptive beamformer

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

Robust adaptive beamforming algorithm based on neural network

Abstract: Adaptive beamforming is known to have resolution and interference rejection capability when the array steering vector is precisely known. However, the performance of adaptive beamforming techniques may degrade severely in the presence of mismatches between the assumed array response and the true array response. In this paper, we propose a novel neural network approach to robust adaptive beamforming. The proposed algorithm is based on explicit modeling of uncertainty in the desired signal array response and a three-layer radial basis function neural network (RBFNN), which belongs to the class of diagonal loading approaches. In the proposed algorithm, the computation of the optimum weight vector is viewed as a mapping problem, which can be modeled using a RBFNN trained with input/output pairs. The proposed algorithm has nearly optimal performance under good conditions, provides the robustness against the signal steering vector mismatches and makes the mean output array SINR consistently close to the optimal one. Simulation results validate substantial performance improvements relative to other adaptive beamforming methods.

Imaging system and method

Abstract: This invention relates generally to non-destructive testing and in particular to ultrasound imaging. A adaptive beamforming imaging method of operating a portable ultrasound imaging system having an array of transducer elements is disclosed. The method comprises transmitting a plurality of beamforming ultrasound signals with each transmission using a different sub-aperture of the array; receiving a reflected ultrasound signals and producing DAS (Delay and Sum) beamforming under each individual sub-aperture transmission. Meanwhile, a coherency factor was calculated based on the proportion of coherent energy in the received time delayed signals from each sub-aperture transmission. All beamforming imaging under defined sub-aperture transmissions were adaptive coherent weighted and synthetised into the final beamforming output. The presented method enables a portable imaging system generating imaging with good quality clarity, contrast and resolution; but less complex hardware and low calculating requirements.

Properties of a general quaternion-valued gradient operator and its applications to signal processing

Abstract: The gradients of a quaternion-valued function are often required for quaternionic signal processing algorithms. The HR gradient operator provides a viable framework and has found a number of applications. However, the applications so far have been limited to mainly real-valued quaternion functions and linear quaternionvalued functions. To generalize the operator to nonlinear quaternion functions, we define a restricted version of the HR operator, which comes in two versions, the left and the right ones. We then present a detailed analysis of the properties of the operators, including several different product rules and chain rules. Using the new rules, we derive explicit expressions for the derivatives of a class of regular nonlinear quaternion-valued functions, and prove that the restricted HR gradients are consistent with the gradients in the real domain. As an application, the derivation of the least mean square algorithm and a nonlinear adaptive algorithm is provided. Simulation results based on vector sensor arrays are presented as an example to demonstrate the effectiveness of the quaternion-valued signal model and the derived signal processing algorithm.

Joint Robust Transmit/Receive Adaptive Beamforming for MIMO Radar Using Probability-Constrained Optimization

Abstract: In this letter, a joint robust transmit/receive adaptive beamforming for multiple-input multiple-output (MIMO) radar based on probability-constrained optimization approach is developed in the case of Gaussian and arbitrary distributed mismatches present in both the transmit and receive signal steering vectors. A tight lower bound of the probability constraint is also derived by using duality theory. The formulated probability-constrained robust beamforming problem is nonconvex and NP-hard. However, we reformulate its cost function into a bi-quadratic function while the probability constraint splits into transmit and receive parts. Then, a block coordinate descent method based on second-order cone programming is developed to address the biconvex problem. Simulation results show an improved robustness of the proposed beamforming method as compared to the worst-case and other existing state-of-the-art joint transmit/receive robust adaptive beamforming methods for MIMO radar.

Adaptive Target Detection Techniques for OFDM-Based Passive Radar Exploiting Spatial Diversity

Abstract: Recently, the benefit of using a channel-based detector (CHAD) with a passive radar exploiting orthogonal frequency division multiplexing waveforms radiated, e.g., by DVB-T transmitters of opportunity has been studied. When multiple antennas are available on receive, we state that CHAD can be seen as space–time array-processing performing on a particular coherent frequency datacube. Building on this new interpretation, we propose an improved version of CHAD in the form of fully dimensional space–time adaptive processing (STAP). Optimization of the signal-to-interference-plus-noise ratio is obtained combining a linearly constrained minimum variance space–time adaptive beamforming and a least squares spatial adaptive filtering. Unlike classical STAP approaches, no training data are used here and only one space–time sample matrix inversion is required. The computational load is then highly reduced allowing a practical deployment. Moreover, since no beamscan in space is performed, the knowledge of array characteristics is not required and the performance shall not be impacted by any calibration errors. Finally, all the target returns being located in a single 2D (range-Doppler) surveillance map, the detection process is then simplified. Results on experimental data show the interests of this new surveillance scheme: No need for a prior rejection of the dominant interference, systematic reduction of secondary lobes, and discrimination of slow moving targets.