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Wideband adaptive beamforming with LCMV. a Subband adaptive beamforming in the frequency domain. b Whole band adaptive beamforming in the time domain. c Subband adaptive beamforming in the time domain. d Adaptive beamforming with the TDL filter
Source publication
In this paper, the performance loss caused by the aperture fill phenomena and heavy computational burden in broadband adaptive beamforming (ADBF) is analyzed, and an efficient approach based on frequency–space cascade processing is presented. First, a digital compensation method is applied to compensate for the aperture fill time of the broadband p...
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In this paper, we propose an adaptive beamforming algorithm for large uniform linear arrays (ULAs), where only a nested subarray is utilized to calculate the beamforming coefficients for the original ULA. In this algorithm, the steering vectors and powers of the signal-of-interest (SOI) and interferences are firstly estimated using the Capon spatia...
Citations
... Since the performance of the algorithm is limited by the number of subbands and its jamming cancellation capability should be weighed with more calculations brought by the increase in bandwidth. Meanwhile, desired signals with high amplitude are prone to the problem of signal cancellation [6,7] and cause beam distortion. ...
—In this paper, an efficient wideband array adaptive beamforming (ADBF) approach based on keystone transform is presented. In order to eliminate the aperture effect of the wideband signal, the modified keystone transform is applied to remove the time delay between different array elements. Thus, the wideband array is equivalent to a narrowband array, and the orthogonal projection matrix of the target steering vector can be used to filter the desired signal in the training samples, which avoids the signal cancellation caused in the estimation of ADBF covariance matrix. Compared with the established algorithm of sliding window, this approach can significantly reduce the computational burden. The feasibility and effectiveness of the proposed method are validated through numerical simulations.
... According to the linearly constrained minimum variance (LCMV) criterion [5,11,13], can be used as a multiconstraint matrix. The weight of the MLCMV filter for the mth subband should satisfy the following: ...
The phase-only transmit nulling method is widely used in narrowband arrays, but there are few reports of its application in wideband arrays. This paper describes the implementation of adaptive transmit nulls in wideband arrays based on subband phase-only pattern synthesis behind each array element. The filter bank behind each array element partitions the transmit signal into independent subbands and utilizes a phase shifter group in each subband to form frequency invariant spatial nulls in the array’s transmit pattern. The scheme developed in this paper includes an algorithm for computing a wideband phase-only weight vector and a subband phase-only adaptive signal processing method based on band partitioning. The validity of the scheme is proven by theoretical analysis and simulation experiments.
... Most of traditional wideband beamforming techniques can work effectively and achieve satisfactory output signal-to-interference-plus-noise ratio (SINR) with the exact formulation of array manifold [13,21]. However, in practice, there are always some mismatches between the assumed array manifold and the actual one, which are caused by the direction of arrival (DOA) error, sensor location error, local scattering effect, and wavefront distortion [4,10,11,22]. The performance of beamformers can be deteriorated severely by these mismatches, especially the DOA error and sensor location error. ...
The performance of the existing robust beamformers can be still degraded by the bias between the nominal steering vector and the actual one. In this paper, a novel robust wideband beamformer based on the time–frequency distributions is proposed, which can estimate the steering vector accurately even in the presence of direction and sensor location errors. Firstly, it develops an approach for wideband signals to select the single-source auto-source time–frequency (TF) points of the source signals. Then these TF points are utilized to obtain the steering vectors without using the perturbed array manifold and direction information. Finally, a higher output signal-to-interference-plus-noise ratio (SINR) is achieved for the minor bias between the estimated steering vectors and the actual ones. Simulation results demonstrate that the proposed algorithm outperforms other conventional robust beamforming approaches and can achieve high output SINR close to the ideal beamformer over a broad range of direction and sensor location errors.
The radar detection of high-speed Unmanned Aerial Vehicle (UAV) swarms has gained a lot of popularity in military field. However, the high-speed and high-density features of UAV swarms could introduce challenges in accurately detecting them, including low Signal-to-Noise Ratio (SNR), Range Migration (RM), Doppler Frequency Migration (DFM), insufficient angular resolution, and false alarms. This paper provides a comprehensive approach by combining a long-time coherent integration method with a super-resolution method. Firstly, Second-order Keystone Transform and General De-chirping Process (SKT-GDP) as well as beamforming is applied to integrate signal in range-doppler-space dimension, so the SNR can be enhanced. Then, Frequency-Selective Reweighted Atomic-norm Minimization (FS-RAM) gridless method is modified to efficiently estimate the precise direction of targets in a single angular unit. Thirdly, the source number estimation accuracy is improved through employing a designed strategy to eliminate ghost targets, i.e., Ghost Target Elimination (GTE), following with the CLEAN process to detect the rest targets. Finally, the effectiveness and detection accuracy of the proposed method is verified through several simulations.
