Minimum Variance Distortionless Response Algorithm Research Articles

Distortion‐less carrier phase tracking space‐time adaptive processor based on power inversion criterion for GNSS anti‐jamming receiver

AbstractSpace‐time adaptive processor (STAP) has been widely used for global navigation satellite system (GNSS) anti‐jamming receiver due to its good anti‐jamming performance. When direction of satellite is unknown, STAP can be implemented based on power inversion (PI) criterion. However, existing space‐time PI algorithm will introduce tens to hundreds of degrees biases into carrier phase, and sometimes will even cause cycle slips, which will reduce the success rate of ambiguity resolution, ultimately deteriorating positioning accuracy. A distortion‐less carrier phase tracking space‐time PI algorithm is proposed. The main novelty is that the proposed algorithm keeps the coefficients of the temporal taps as real values by imposing constraints on the weights of the antenna array. Several experiments are implemented to verify the effectiveness of the proposed algorithm. For comparison, the results of PI algorithm and minimum variance distortion‐less response (MVDR) algorithm are shown. Results show that when the number, style, and direction of interferences and the direction of GNSS signal vary, different degrees of biases are introduced into carrier phases for the PI and the MVDR algorithm. However, no bias is introduced into the proposed algorithm. As a result, the effectiveness of the proposed algorithm is verified.

SATCOM Earth Station Arrays Anti-Jamming Based on MVDR Algorithm

In modern life, a large amount of information is transmitted through satellites. The anti-jamming ability of satellite communication earth stations is the basis for ensuring the smooth flow of information. In the case that multiple small earth stations cannot communicate due to jamming, the minimum variance distortionless response (MVDR) algorithm based on reflector antenna array is proposed. Firstly, the gain expression of satellite communication earth station antenna is derived, and the mathematical model of the received signal of the reflector antenna array is established. Then, the MVDR beamforming algorithm based on the reflector antenna is proposed and applied to the satellite communication earth station reflector antenna array, and the anti-jamming capability of the reflector antenna array using this algorithm is analyzed through simulation. The simulation results show that the earth station reflector antenna array using MVDR algorithm can effectively achieve array gain of the direction of the satellite signal, suppress the jamming signals, increase the output signal to interference plus noise ratio (SINR) of the reflector antenna array, and increase the output signal to jamming plus noise ratio with the increase in the number of snapshots.

Direction of Arrival Estimation for Single Microelectromechanical Systems Vector Hydrophone Using Modified Wavelet Packet De-Noising

The complex and variable ocean environment introduces complex noise to the signal received by microelectromechanical systems (MEMS) vector hydrophones, which seriously affects target location. To improve the detection efficiency and broaden the application range of vector hydrophone, this paper proposed a novel modified Wavelet packet de-noising method, known as the Wavelet packet energy (WPE) de-noising method. This method utilizes Shannon entropy to determine the optimal decomposition levels of Wavelet packets, and calculates the energy of reconstructed signals in each frequency band to construct feature vectors. The Wavelet packet with the larger energy is selected to reconstruct the signal until the root mean square error of the original signal and the reconstructed signal is minimized. thereby obtaining an optimal solution. The performance of this proposed method is evaluated through both indoor and outdoor experiments. The experimental results demonstrate that the developed method is effective in Direction of Arrival (DOA) estimation of single frequency signals and is feasible in low signal-to-noise ratio situations. The method improves the azimuth discrimination ability of the Minimum Variance Distortionless Response algorithm, and DOA estimation errors are all within 1°. Furthermore, the indoor and outdoor experiments also demonstrate that the WPE de-noising method solves the group delay and distortion of signals caused by conventional filtering.

Anti-Jamming Method and Implementation for GNSS Receiver Based on Array Antenna Rotation

Global navigation satellite system (GNSS) array antenna receivers are effective for suppressing wideband jamming. However, its anti-jamming performance decreases sharply when the number of wideband interference surpasses the number of array elements. Since a large number of jammers are often used in navigation countermeasures, it is crucial to keep array antenna receivers available in such conditions. Aiming at this issue, two main tasks were performed in this research and are presented in this paper: Firstly, the direction sensitivity of the sup-freedom anti-jamming performance is revealed and an anti-jamming method for array antenna receivers based on antenna rotation is proposed. Secondly, in order to determine the optimal rotation angle rapidly, a variable-step iteration algorithm based on gradient descent is proposed. Theoretical analysis and simulation show the effectiveness of the proposed anti-jamming method and the efficiency of the implementation algorithm. In a typical airborne scenario with a maximum azimuth difference of 90°, the anti-jamming ability of the proposed method improved by 21~26 dB and 5~10 dB for arrays adopting the PI (power inversion) and MVDR (minimum variance distortionless response) algorithms, respectively. The iterative efficiency improved by 78.35–99.63% in comparison with a traversal of 0.1° search resolution. The proposed method and algorithm are not limited to airborne scenarios and they might be influential to anti-jamming algorithms in the data domain.

Performance analysis of repeater spoofing suppression based on GNSS multi-beam receiver

In order to analyze the anti-spoofing performance of the Global Navigation Satellite System (GNSS) multi-beam anti-jamming receiver in the presence of direct repeater spoofing, this paper deduces the theoretical formulas of the output real signal and the direct repeater spoofing signal power of the multi-beam anti-jamming receiver using the minimum variance distortionless response (MVDR) algorithm, when the number of snapshots is limited. The influence of the power of the spoofing signal reaching the surface of the antenna array on the output power of the real signal and the spoofing signal is analyzed in detail. The analysis shows that no matter how the power of the direct repeater spoofing signal is set, the multi-beam anti-jamming receiver using the MVDR algorithm can always suppress the spoofing below the real signal power level, and the suppression effect is more significant when the spoofing signal-to-noise ratio is high. Finally, the correctness of the conclusion is verified by simulation.

Clustering Analysis Algorithm of Volleyball Simulation Based on Radial Fuzzy Neural Network

Aiming at a series of problems existing in volleyball, based on radial fuzzy neural network theory, the optimized simulation clustering analysis algorithm is used to monitor and analyze volleyball. By analyzing the feature weights of nodes at different stages, the optimal radial fuzzy neural network was constructed, which was combined with the simulation clustering algorithm to obtain the relevant optimization model describing volleyball. The accuracy of the optimization model is verified by comparing with the original model. The results show that with the increase of response, the response curves of different algorithms show fluctuation. Among them, the fluctuation range of MPDR (minimum power distortionless response) algorithm is larger, and the value of the curve obtained by MVDR (minimum variance distortionless response) algorithm differs greatly from that of the optimization algorithm at some key nodes, while the beam changing chart obtained by the optimization algorithm can better reflect the changing trend of the beam. Model indexes under different algorithms are different. When the number of iterative steps is less than 30, indexes under different algorithms are all greater than the standard value. When the number of iterations is more than 30, the indexes under different algorithms are all less than the standard value. Through verification, it can be seen that the original model can only describe the first stage of volleyball, while the optimization model can describe the whole process of volleyball. It shows that the optimization model can be used to describe and analyze volleyball-related data. And the algorithm can be used to better predict and analyze volleyball, and the analysis results can provide relevant guidance for volleyball. The optimization model provides basis and theoretical support for the application of volleyball simulation clustering algorithm, so as to better promote volleyball and better guide the movement.

Minimum variance Lamb wave imaging based on weighted sparse decomposition coefficients in quasi-isotropic composite laminates

Lamb wave is a promising means for active structural health monitoring and nondestructive evaluation of laminated composite plates. The inevitable reflections from structural geometric boundaries and other interferences limits the imaging performance of many existing imaging methods. The image generated through the well-known delay-and-sum method holds a wide mainlobe width and high level of sidelobes. Although the sparse reconstruction method is free from those deficiencies, it is sensitive to the regularization parameter. To overcome those limitations, a Lamb wave imaging method to locate anomalies or damage in laminated composite plates is proposed. The scattering signals are sparsely decomposed one by one with a prior weights penalized on the undetermined sparse coefficients, and the minimum variance distortionless response algorithm is adopted to process those sparse coefficients so as to generate the image. Experimental results on a quasi-isotropic laminated composite plate demonstrate the effectiveness of the proposed method.

Antenna’s beamformer design for diagnosed breast cancer image by composites test-beds

Radiologyanalysis of breast cancer that appears through the Minimum Variance Distortion-less Response (MVDR) algorithm, which is presented in this paper.The prime objective ofresearch study isdiagnosticanalysisand developed from Microwave Imaging (MI) system for radiology pictorial image. The collections of scattered signals have measured by Agilent Microwave analyzer (N99917A) in the composite test-beds. The test-bed consists of broadband antennas, which weariedto biological equivalent breast homogeneous model, excitation and reception ports coupled with Agilent analyzer. Therefore, the Received Signal Strength (RSS) is achieved from reception port via Directional of Arrival (DOA) of excitation port. Hence, the two dimensional Power Spectral Density (PSD) obtained using MVDR Algorithm. Therefore, these results have validated by existing Debye test-beds.

Speech Intelligibility and Spatial Release From Masking Improvements Using Spatial Noise Reduction Algorithms in Bimodal Cochlear Implant Users.

This study investigated the speech intelligibility benefit of using two different spatial noise reduction algorithms in cochlear implant (CI) users who use a hearing aid (HA) on the contralateral side (bimodal CI users). The study controlled for head movements by using head-related impulse responses to simulate a realistic cafeteria scenario and controlled for HA and CI manufacturer differences by using the master hearing aid platform (MHA) to apply both hearing loss compensation and the noise reduction algorithms (beamformers). Ten bimodal CI users with moderate to severe hearing loss contralateral to their CI participated in the study, and data from nine listeners were included in the data analysis. The beamformers evaluated were the adaptive differential microphones (ADM) implemented independently on each side of the listener and the (binaurally implemented) minimum variance distortionless response (MVDR). For frontal speech and stationary noise from either left or right, an improvement (reduction) of the speech reception threshold of 5.4 dB and 5.5 dB was observed using the ADM, and 6.4 dB and 7.0 dB using the MVDR, respectively. As expected, no improvement was observed for either algorithm for colocated speech and noise. In a 20-talker babble noise scenario, the benefit observed was 3.5 dB for ADM and 7.5 dB for MVDR. The binaural MVDR algorithm outperformed the bilaterally applied monaural ADM. These results encourage the use of beamformer algorithms such as the ADM and MVDR by bimodal CI users in everyday life scenarios.

Distortionless pseudo‐code tracking space–time adaptive processor based on the PI criterion for GNSS receiver

Space–time adaptive processor based on power inversion (PI) criterion can effectively suppress interference for the global navigation satellite system (GNSS) receiver when the steering vector of the GNSS signal is unknown. However, existing space–time PI processing methods will introduce meter-level pseudo-code tracking biases into the GNSS receiver measurements which cause several meter-level position errors. A distortionless pseudo-code tracking space–time PI algorithm is proposed. It could not only suppress interference, but also introduce no pseudo-code tracking biases. The major novelty of the proposed method is ensuring the symmetry of the output signal's cross-correlation function by constraining coefficients. Several experiments are implemented to test the performance of the proposed algorithm. For comparison, the results of the PI algorithm and the minimum variance distortionless response (MVDR) algorithm are also shown. Results show that for the PI algorithm and the MVDR algorithm, pseudo-code tracking biases are introduced in different experiments; however, for the proposed algorithm, there are no pseudo-code tracking biases in those experiments. As a result, the effectiveness of the proposed method is verified.

Robust Modified MVDR Scheme Using Chirp Signal for Direction of Arrival Estimation

This research is about an effort to increase the robustness of the Minimum Variance Distortionless Response (MVDR) algorithm to noise by using a chirp signal for direction of arrival estimation (DoA). DoA is a part of radar capability to estimate the angle of arrival on the object under observation. The conventional MVDR as proposed by J. Capon, was designed to work with the monochromatic sinusoidal signal. Even though the conventional MVDR work on low SNR up to 0 dB, however, the conventional method does not work well if chirp signal is used instead of monochromatic sinusoidal signal. The usage of MVDR chirp signal is essential in the case of a very low SNR environment such as in long distance object detection, which is typically more than 10 km. The problem to be solved in this research is how to modify the MVDR algorithm so that it can work well on chirp signal. In this research we offer a modified MVDR algorithm by adding the matched filter and the phase detector components before the MVDR algorithm is applied. Matched filter is responsible for the timing of the chirp signal detection, and the phase detector is to estimate the time delay estimation of each chirp signal from each antenna with a reference signal, which correspond to the phases. Based on the phase estimation, sinusoidal signal is generated and fed to the MVDR algorithm. On the technical aspect, the chirp signal is sent intermittently with a duration of 100 ?s and repeated in time interval of 1 ms. The antenna sensor using an array of Uniform Linear Array (ULA) which consist of N-elements. Computer simulation shows that the modified MVDR using the chirp signal improve the robustness of the algorithm up to -30 dB, while on the other hand the classical MVDR works only up to 0 dB SNR. -30 dB of SNR is the minimum requirement of 3D Radar existing.

MATLAB-Based GPU Acceleration for Multiple-Input and Multiple-Output Radar Beamforming Algorithm

Multi-input and multi-output (MIMO) radar systems possess numerous advantages, such as scanning an entire region much faster than a phased array, enhancing the spatial resolution, mitigating interference and multipath fading, and improving the probability of detection of targets. MIMO radar systems use adaptive beamforming techniques such as the minimum variance distortionless response (MVDR) to obtain the best possible estimation of the direction of arrival (DOA) of the targets. The MVDR algorithm has been thoroughly investigated for traditional phased array radars. For MIMO radar systems, however, it requires significant signal processing, which can introduce substantial latency, especially in the case of large MIMO systems where few hundred antennas are used; this can be solved by using a Graphics Processor Unit (GPU), which contains thousands of cores and can execute many operations in parallel. This paper presents a MATLAB-based approach for GPU parallelization of the minimum variance distortionless (MVDR) beamforming algorithm in a MIMO radar system. Two MIMO radar systems are considered. The first one is a simulated MIMO radar which is used for automotive adaptive cruise control (ACC), and the second one is an experimental monostatic MIMO radar that is based on a vector network analyzer (VNA). It is shown that the GPU achieved a speedup of up to 7 times while successfully detecting all targets.

Damage imaging for composite using Lamb wave based on minimum variance distortion-less response method

It is highly probable for the structures of carbon fiber reinforced plastics (CFRP) to suffer from invisible impact damage, for which the identification of such damage is of great significance. For the purpose of damage localization, this paper proposes a minimum variance distortion-less response (MVDR) algorithm that employs linear array sensor. In addition, a near field signal model based on active Lamb wave is established and the propagation of Lamb wave is investigated in composite laminates through the method of simulation. Moreover, a damage imaging system is also set up for composites to verify the effectiveness of the MVDR algorithm. Besides, in the study, wavelet transform is used as well to extract narrowband signals and promote signal-to-noise. It is shown by the results that the proposed algorithm can accurately identify the location of damage through the method of imaging. It is concluded that the maximum error of damage identification is 1.2 cm and MVDR algorithm has great potential in the field, damage imaging of composite materials. As a result, it provides a novel idea for damage imaging of composite materials.

Direction of arrivals estimation for correlated broadband radio signals by MVDR algorithm using wavelet

A theoretical relationship between the wavelet transform and the fast fourier transformation (FFT) methods in broadband wireless signal is proposed for solving the direction of arrivals (DOAs) estimation problem. This leads naturally to the derivation of minimum variance distortionless response (MVDR) algorithm, which combines the benefits of subspace methods with those of wavelet, and spatially smoothed versions are utilized which exhibits good performance against correlated signals. We test the method's performance by simulating and comparing the performance of proposed algorithm, FFT MVDR and MVDR with correlated signals, and an improved performance is obtained.

MVDR Algorithm Based on Estimated Diagonal Loading for Beamforming

Beamforming algorithm is widely used in many signal processing fields. At present, the typical beamforming algorithm is MVDR (Minimum Variance Distortionless Response). However, the performance of MVDR algorithm relies on the accurate covariance matrix. The MVDR algorithm declines dramatically with the inaccurate covariance matrix. To solve the problem, studying the beamforming array signal model and beamforming MVDR algorithm, we improve MVDR algorithm based on estimated diagonal loading for beamforming. MVDR optimization model based on diagonal loading compensation is established and the interval of the diagonal loading compensation value is deduced on the basis of the matrix theory. The optimal diagonal loading value in the interval is also determined through the experimental method. The experimental results show that the algorithm compared with existing algorithms is practical and effective.

Minimum Variance Approaches to Ultrasound Pixel-Based Beamforming.

We analyze the principles underlying minimum variance distortionless response (MVDR) beamforming in order to integrate it into a pixel-based algorithm. There is a challenge posed by the low echo signal-to-noise ratio (eSNR) when calculating beamformer contributions at pixels far away from the beam centreline. Together with the well-known scarcity of samples for covariance matrix estimation, this reduces the beamformer performance and degrades the image quality. To address this challenge, we implement the MVDR algorithm in two different ways. First, we develop the conventional minimum variance pixel-based (MVPB) beamformer that performs the MVDR after the pixel-based superposition step. This involves a combination of methods in the literature, extended over multiple transmits to increase the eSNR. Then we propose the coherent MVPB beamformer, where the MVDR is applied to data within individual transmits. Based on pressure field analysis, we develop new algorithms to improve the data alignment and matrix estimation, and hence overcome the low-eSNR issue. The methods are demonstrated on data acquired with an ultrasound open platform. The results show the coherent MVPB beamformer substantially outperforms the conventional MVPB in a series of experiments, including phantom and in vivo studies. Compared to the unified pixel-based beamformer, the newest delay-and-sum algorithm in [1], the coherent MVPB performs well on regions that conform to the diffuse scattering assumptions on which the minimum variance principles are based. It produces less good results for parts of the image that are dominated by specular reflections.

Minimum variance imaging based on correlation analysis of Lamb wave signals

In Lamb wave imaging, MVDR (minimum variance distortionless response) is a promising approach for the detection and monitoring of large areas with sparse transducer network. Previous studies in MVDR use signal amplitude as the input damage feature, and the imaging performance is closely related to the evaluation accuracy of the scattering characteristic. However, scattering characteristic is highly dependent on damage parameters (e.g. type, orientation and size), which are unknown beforehand. The evaluation error can degrade imaging performance severely. In this study, a more reliable damage feature, LSCC (local signal correlation coefficient), is established to replace signal amplitude. In comparison with signal amplitude, one attractive feature of LSCC is its independence of damage parameters. Therefore, LSCC model in the transducer network could be accurately evaluated, the imaging performance is improved subsequently. Both theoretical analysis and experimental investigation are given to validate the effectiveness of the LSCC-based MVDR algorithm in improving imaging performance.

Direction of Arrival Estimation in Linear Arrays by a Novel Hybrid Algorithm

In this study, a new hybrid algorithm for uniform linear antenna (ULA) array was composed by using First Order Forward Prediction (FOFP) and the Minimum Variance Distortionless Response (MVDR) algorithms together. FOFP and MVDR algorithms were discussed as incident signal direction prediction algorithms. The powerful and weak points of these two algorithms were explained. Some scripts were written by using MATLAB. 5 antennas which were spaced with half wavelength, forms an ULA array. Its output data was used as input data of the three algorithms mentioned above. The results obtained from the hybrid algorithm and the individual results of MVDR and FOFP algorithms were compared under the same conditions. An improvement in the proposed hybrid algorithm is observed.

Recursive Sparsity-based MVDR Algorithm for Interference Cancellation in Sensor Arrays

ABSTRACTIn this paper, an improved sparsity-based interference cancellation algorithm for beamforming in sensor arrays is proposed, which improves the conventional Minimum Variance Distortionless Response (MVDR) algorithms. The key point in this algorithm is to divide the stress on the minimum variance term in the conventional algorithms with a term that uses no additional information than those used in conventional algorithms. The goal in this algorithm is to find the sparsest array response in the angles other than the Direction Of Arrival (DOA) of the Signal Of Interest (SOI). Also, a global convergence proof for this algorithm is presented. The results show that by this algorithm, some reduction in sidelobe levels, deeper nulls, less sensitivity to the DOA of the SOI and no sensitivity to data length are achieved.

Detection of Multiple R/C Devices Using MVDR and Genetic Algorithms

Reflections, multipath propagation, and scattering creates phantom sources of signal. In addition, reliable detection of radio controlled (RC) devices in the presence of multiple actual devices is a challenging task. RC devices employing super regenerative receivers (SRRs) and super heterodyne receivers emit unintended radiations in their ON-state. This paper introduces a novel detection scheme that combines self-similarity and received signal strength indicator (RSSI)-based detection with minimum variance distortionless response (MVDR) method. In addition, detection accuracy is improved using multiconstrained genetic algorithms (GAs). RSSI method detects multiple devices from received signal strength and Hurst parameter identifies self-similar SRR devices. Regularized MVDR improves detection of multiple devices by jamming unwanted signals and signals from known angle of arrival. Regularization reduces variation in detection due to environmental noise. Multiconstrained GA is implemented in the cases where MVDR fails. The experimental results for detection have also been presented for multiple SRR receivers (door bells at 315 MHz).