scholarly journals Improved Mainlobe Interference Suppression Based on Blocking Matrix Preprocess

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Jie Yang ◽  
Congfeng Liu
Keyword(s):  
Covariance Matrix ◽  
Interference Suppression ◽  
Adaptive Beamforming ◽  
Linear Constraints ◽  
Diagonal Loading ◽  
Loading Level ◽  
Blocking Matrix ◽  
Simulation Results ◽  
Matrix Mismatch ◽  
Selection Of

For the problem of mainlobe direction shifting that is caused by the mainlobe interference suppression based on blocking matrix preprocess, an effective method is proposed which is based on the combination of diagonal loading and linear constraints. Therein, the reason for mainlobe direction shifting is analyzed and found to be that the covariance matrix mismatch exists in the realization of the adaptive beamforming. Therefore, the diagonal loading processing is used to overcome the mismatch and correct the mainlobe direction shifting, and the linear constraints are used to make sure of the beam pattern nulling in the interference directions; then the desired performance of adaptive beamforming is obtained. Simulation results attest the correctness and effectiveness of the proposed method, and they also show that the proposed method is insensitive to the selection of diagonal loading level, which means the loading factor is easy to choose.

scholarly journals Robust Adaptive Beamforming against Signal Steering Vector Mismatch and Jammer Motion

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaojun Mao ◽  
Wenxing Li ◽  
Yingsong Li ◽  
Yaxiu Sun ◽  
Zhuqun Zhai
Keyword(s):  
Adaptive Beamforming ◽  
Projection Matrix ◽  
Diagonal Loading ◽  
Steering Vector ◽  
Output Performance ◽  
Sample Covariance ◽  
Steering Vector Mismatch ◽  
Simulation Results ◽  
Robust Adaptive ◽  
Analytical Expressions

Since adaptive beamformer suffers from output performance degradation in the presence of interference nonstationarity and signal steering vector mismatch, a novel robust null broadening adaptive beamforming is proposed. The proposed method is realized by the combination of projection transform and diagonal loading techniques. First, a new projection matrix with null broadening ability is constructed and then projects the array received data onto the projection matrix. With the diagonal loading technique, a new sample covariance matrix is obtained. The theoretical analysis shows that the projection transform operation can expand the incident direction of the interference and improve orthogonality between the signal-plus-interference and the noise subspaces; thus the proposed beamformer can effectively broaden the jammer null and enhance the null depth. The analytical expressions of the proposed algorithm are also provided, which are efficient and easily solved. Simulation results are presented and demonstrated that the proposed beamformer can provide strong robustness against signal steering vector mismatch and jammer motion.

scholarly journals Low-Complexity Robust Adaptive Beamforming Based on INCM Reconstruction via Subspace Projection

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7783
Author(s):  
Yanliang Duan ◽  
Xinhua Yu ◽  
Lirong Mei ◽  
Weiping Cao
Keyword(s):  
Covariance Matrix ◽  
Minimum Mean Square Error ◽  
Low Complexity ◽  
Training Sequence ◽  
Adaptive Beamforming ◽  
Projection Matrix ◽  
Robust Adaptive Beamforming ◽  
Sample Covariance ◽  
Blocking Matrix ◽  
Robust Adaptive

Adaptive beamforming is sensitive to steering vector (SV) and covariance matrix mismatches, especially when the signal of interest (SOI) component exists in the training sequence. In this paper, we present a low-complexity robust adaptive beamforming (RAB) method based on an interference–noise covariance matrix (INCM) reconstruction and SOI SV estimation. First, the proposed method employs the minimum mean square error criterion to construct the blocking matrix. Then, the projection matrix is obtained by projecting the blocking matrix onto the signal subspace of the sample covariance matrix (SCM). The INCM is reconstructed by replacing part of the eigenvector columns of the SCM with the corresponding eigenvectors of the projection matrix. On the other hand, the SOI SV is estimated via the iterative mismatch approximation method. The proposed method only needs to know the priori-knowledge of the array geometry and angular region where the SOI is located. The simulation results showed that the proposed method can deal with multiple types of mismatches, while taking into account both low complexity and high robustness.

scholarly journals A User Parameter-Free Diagonal-Loading Scheme for Clutter Rejection on Radar Wind Profilers

2017 ◽  
Vol 34 (5) ◽  
pp. 1139-1153 ◽  
Author(s):  
Taishi Hashimoto ◽  
Koji Nishimura ◽  
Masaki Tsutsumi ◽  
Kaoru Sato ◽  
Toru Sato
Keyword(s):  
Signal To Noise Ratio ◽  
Adaptive Beamforming ◽  
Diagonal Loading ◽  
Loading Level ◽  
Ground Clutter ◽  
Two Factors ◽  
Robust Adaptive ◽  
Using Data ◽  
The Stability ◽  
Wind Profilers

AbstractThis paper presents a novel method for the automatic determination of the diagonal-loading level for robust adaptive beamforming on radar wind profilers. This method balances the degradation of the signal-to-interference ratio with that of the signal-to-noise ratio to maximize the detectability of the backscattered signals. Because radial wind velocities are usually estimated from the first moment of the spectrum of backscattered echoes, both the residual ground clutter and any increase in noise level degrade the detectability of atmospheric echoes. The proposed algorithm evaluates the power spectral density of the residual clutter and increased noise to determine the optimal diagonal-loading level by balancing these two factors. The results of numerical simulation show that, without the need to specify any user parameters, the proposed algorithm is stable and more effective at maximizing the signal-to-interference ratio than the conventional norm-constrained diagonal-loading approach. The stability and clutter suppression capability of the proposed algorithm are examined using data from the Program of the Antarctic Syowa Mesosphere–Stratosphere–Troposphere/Incoherent Scatter Radar.

scholarly journals Robust adaptive beamforming with enhancing the interference suppression capability

2019 ◽  
Vol 8 ◽  
Author(s):  
Linxian Liu ◽  
Yang Li
Keyword(s):  
Performance Optimization ◽  
Signal To Noise Ratio ◽  
Interference Suppression ◽  
Adaptive Beamforming ◽  
Training Data ◽  
Worst Case ◽  
Diagonal Loading ◽  
Steering Vector ◽  
Robust Adaptive Beamforming ◽  
Robust Adaptive

AbstractThe steering vector mismatch causes signal self-nulling for adaptive beamforming when the training data contain the desired signal component. To prevent signal self-nulling, many beamformers use robust technology, which is usually equivalent to the diagonal loading approach. Unfortunately, the diagonal loading approach achieves better signal enhancement at the cost of losing its interference suppression capability, especially at high input signal-to-noise ratio. In this paper, a novel robust adaptive beamforming method is developed to improve the interference suppression capability. The proposed beamformer is based on the worst-case performance optimization technology with a new estimated steering vector and a special set parameter. Firstly, a subspace which is orthogonal to the interference's steering vector is obtained by using the interference-plus-noise covariance matrix; then a new steering vector which is orthogonal to each interference's steering vector is estimated; finally, the beamformer's weight is solved with the worst-case performance optimization technology with a special set parameter. Theoretical analysis of the interference suppression principle is analyzed in detail, and some simulation results are presented to evaluate the performance of the proposed beamformer.

Target Localization for Distributed Multiple-Input Multiple-Output Radar Using Capon Algorithm with Diagonal Loading

2012 ◽  
Vol 229-231 ◽  
pp. 1599-1604
Author(s):  
Jin Li Chen ◽  
Jia Qiang Li ◽  
Yan Ping Zhu
Keyword(s):  
High Resolution ◽  
Covariance Matrix ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Target Localization ◽  
Diagonal Loading ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Simulation Results ◽  
High Level

The distributed multiple-input multiple-output (MIMO) radar can achieve the high- resolution capabilities of target localization by coherent processing, far exceeding the bandwidth-dependent resolution of traditional radar. The conventional beam former synchronizing the phase across the widely separated transmitting and receiving antennas creates high level sidelobes that causes ambiguity in target localization. The Capon beam former with lower level sidelobes for target localization suffers from the irreversible of the covariance matrix when the numbers of transmitting and receiving antennas increase. Thus, the Capon algorithm with diagonal loading is applied to distributed MIMO radar for target localization with lower level sidelobes. Simulation results are presented to verify the effectiveness of the proposed method.

Enhanced Spectrum Sensing Algorithm Based on MME Detection and OAS Shrinkage Estimator

2019 ◽  
Vol 10 (1) ◽  
pp. 83-97
Author(s):  
Amoon Khalil ◽  
Mohiedin Wainakh
Keyword(s):  
Cognitive Radio ◽  
Covariance Matrix ◽  
Spectrum Sensing ◽  
Detection Probability ◽  
Detection Performance ◽  
Shrinkage Estimator ◽  
Detection Window ◽  
Simulation Results

Spectrum Sensing is one of the major steps in Cognitive Radio. There are many methods to conduct Spectrum Sensing. Each method has different detection performances. In this article, the authors propose a modification of one of these methods based on MME algorithm and OAS estimator. In MME&OAS method, in each detection window, OAS estimates the covariance matrix of the signal then the MME algorithm detects the signal on the estimated matrix. In the proposed algorithm, authors assumed that there is correlation between two consecutive decisions, so authors suggest the OAS estimator depending on the last detection decision, and then detect the signal using MME algorithm. Simulation results showed enhancement in detection performance (about 2dB when detection probability is 0.9. compared to MME&OAS method).

An Analysis on the Forming Load of AA 2024 Aluminium Alloy in Combined and Sequence Operation Process

2006 ◽  
Vol 519-521 ◽  
pp. 949-954 ◽  
Author(s):  
Beong Bok Hwang ◽  
J.H. Shim ◽  
Jung Min Seo ◽  
H.S. Koo ◽  
J.H. Ok ◽  
...  
Keyword(s):  
Finite Element ◽  
Load Capacity ◽  
Low Cost ◽  
Forming Load ◽  
Mechanical Press ◽  
Combined Operation ◽  
Aa 2024 ◽  
Load Characteristics ◽  
Simulation Results ◽  
Selection Of

This paper is concerned with the analysis of the forming load characteristics of a forward-backward can extrusion in both combined and sequence operation. A commercially available finite element program, which is coded in the rigid-plastic finite element method, has been employed to investigate the forming load characteristics. AA 2024 aluminum alloy is selected as a model material. The analysis in the present study is extended to the selection of press frame capacity for producing efficiently final product at low cost. The possible extrusion processes to shape a forward-backward can component with different outer diameters are categorized to estimate quantitatively the force requirement for forming forward-backward can part, forming energy, and maximum pressure exerted on the die-material interfaces, respectively. The categorized processes are composed of combined and/or some basic extrusion processes such as sequence operation. Based on the simulation results about forming load characteristics, the frame capacity of a mechanical press of crank-drive type suitable for a selected process could be determined along with securing the load capacity and with considering productivity. In addition, it is suggested that different load capacities be selected for different dimensions of a part such as wall thickness in forward direction and etc. It is concluded quantitatively from the simulation results that the combined operation is superior to sequence operation in terms of relatively low forming load and thus it leads to low cost for forming equipments. However, it is also known from the simulation results that the precise control of dimensional accuracy is not so easy in combined operation. The results in this paper could be a good reference for analysis of forming process for complex parts and selection of proper frame capacity of a mechanical press to achieve low production cost and thus high productivity.

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