MVDR Algorithm Based on Estimated Diagonal Loading for Beamforming

Xiao, Yuteng; Yin, Jun; Qi, Honggang; Yin, Hongsheng; Hua, Gang

doi:10.1155/2017/7904356

Cited by 24 publications

(5 citation statements)

References 12 publications

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“…However, the performance of the MVDR algorithm depends on the accuracy of the covariance matrix, and if there is an imprecise covariance matrix, its performance decreases significantly. In reference [124], the MVDR algorithm is improved by using the estimated diagonal loading. The range of diagonal loading compensation is reduced based on the matrix theory.…”

Section: Mp-densitymentioning

confidence: 99%

A Review on GNSS-Threat Detection and Mitigation Techniques

Sharifi-Tehrani

Ghasemi²

2022

Cloud Computing and Data Science

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Global navigation satellite systems (GNSS) have played an important role in commercial, military and industrial navigation as well as cloud computing, geospatial analysis and digital modeling. Nowadays, with the advancement of science and technology, the capabilities of electronic warfare, including signal jamming, interference, and spoofing, have also advanced. Attacks and threats at simple, intermediate and advanced levels, endanger the security and reliability of GNSS in the commercial, industrial and military fields such as geolocation, geospatial techniques and digital twins. Therefore, coping with this problem and challenge is very important in maintaining security and reliability. At present, various methods and algorithms have been designed and utilized based on statistical properties, moving receiver, artificial array, wavelet transform and etc., each of which has advantages, disadvantages and blind spots. In this paper, the necessity and requirements for dealing with GNSS threats are emphasized, and the most important researches in the field of GNSS threat (jamming/interference/spoofing) detection and mitigation are studied and reviewed. Their advantages and disadvantages are discussed, and improving areas are also proposed.

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Section: Mp-densitymentioning

confidence: 99%

A Review on GNSS-Threat Detection and Mitigation Techniques

Sharifi-Tehrani

Ghasemi²

2022

Cloud Computing and Data Science

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“…Numerous DL methods such as fixed DLL, user parameter-based DL and automatic DLL evaluation methods have been proposed. [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26] As mentioned earlier in section 1, some of the algorithms are ad-hoc based and most of them suffer from one or more drawbacks such as difficulties in evaluation of DLL and choosing of user parameters.…”

Section: Improvement Of Robustnessmentioning

confidence: 99%

Design of DSP ‐based robust antenna beamformer using novel MVDR algorithm: Extension to SLL reduction

Duppala

Misra

Sanyal

2021

Int J RF Mic Comp-Aid Eng

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The mismatch between the actual direction of arrival (DOA) of signal of interest (SOI) and the estimated DOA drastically deteriorates the performance of the antenna beamformer. Diagonal loading (DL) is a popular method to improve the robustness of the antenna beamformer against such mismatch.However, the evaluation of optimum diagonal load level (DLL) involves much complexity. This paper proposes a simple and user parameter free novel data dependent algorithm for the development of minimum variance distortion less response (MVDR) based robust antenna beamformer which provides uniform output SINR over the entire range of mismatch. The behavior of the beamformer for varying DLL has been studied and observed the fact that, under optimum DLL condition, the main lobe of beam pattern is focused towards the estimated DOA of SOI within a mismatch of 4 0 . The novelty includes the logical exploitation of the analogy between the frequency and space domains Fourier Transforms followed by the frequency shift property and convolutions with necessary modifications. Next, the proposed algorithm has been extended to minimize the side lobe level (SLL) below À35 dB, in addition to achieving the desired robustness. Another advantage of this algorithm is the requirement of minimum additional computational burden of M complex multiplications and one convolution. The implementation of the robust antenna beamformer has also been done through the Digital Signal Processor TMS320C5416 supported with Code Composer Studio (CCS) for real time operations. Extensive comparative simulations have been included to justify the superiority of the proposed algorithm over the existing algorithms.

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“…The first type of methods adopts a wide variety of algorithms to estimate the IPNCM from the SCM. To give an illustration, diagonal loading (DL) [4,5] is one of the most fundamental algorithms to strengthen performance. DL algorithm is to add a user-defined scalar to the diagonal element of the SCM.…”

Section: Introductionmentioning

confidence: 99%

“…[14] mitigates the effect of the SCM errors and SVs perturbations by projecting the nominal SV into the signalplus-interference subspace. [5] applies an optimized projection research in order to build up the precision of the covariance matrix reconstruction.…”

Section: Introductionmentioning

confidence: 99%

Robust adaptive beamforming based on covariance matrix reconstruction and SV estimation

Yang

Jiang

2023

Second International Conference on Electronic Information Engineering and Computer Communication (EIECC 2022)

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In this research, we propose an optimized robust Capon beamforming (RCB) algorithm, which is based on covariance matrix reconstruction along with steering vector (SV) estimation. It is crucial to assurance the robustness of the beamforming algorithm performs better. The proposed algorithm indicates an alternative method to roughly estimate the SV of the interference signal, thus we are able to construct the optimal Capon space spectrum. Secondly, the reconstructed interference signal covariance matrix is obtained by integrating the optimized Capon space power spectrum in the corresponding sector of the interference signal. Subsequently, we adopt the eigen decomposition of the sample covariance matrix (SCM)to obtain the noise covariance matrix, as well as complete the reconstruction of the interference-plus-noise covariance matrix (IPNCM). Finally, this paper optimizes the algorithm of uncertainty set constraint, as well as gets more accurate desired signal SV. The numerical simulation results obtained through two hundred Monte-Carlo experiments suggest that the proposed algorithm indicates higher robustness, better noise suppression ability, and higher output SINR, which is closer to the optimal output curve than several traditional RAB algorithms.

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MVDR Algorithm Based on Estimated Diagonal Loading for Beamforming

Cited by 24 publications

References 12 publications

A Review on GNSS-Threat Detection and Mitigation Techniques

A Review on GNSS-Threat Detection and Mitigation Techniques

Design of DSP ‐based robust antenna beamformer using novel MVDR algorithm: Extension to SLL reduction

Robust adaptive beamforming based on covariance matrix reconstruction and SV estimation

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