Maximum Entropy-Based Interference-Plus-Noise Covariance Matrix Reconstruction for Robust Adaptive Beamforming

Mohammadzadeh, Saeed; Nascimento, Vítor H.; Lamare, Rodrigo C. de; Kükrer, Osman

doi:10.1109/lsp.2020.2994527

Cited by 52 publications

(48 citation statements)

References 92 publications

(193 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…But there is no systematic way for deriving the loading factor. The more recent RBF based on Interference plus Noise Covariance (IPNC) Matrix Reconstruction algorithm address this issue by removing the SOI component from IPNC matrix and make a better estimation of SOI based on Capon spatial spectrum weighted reconstruction [20] or Maximum Entropy Power Spectrum (MEPS) weighted reconstruction [21]. But it requires expensive matrix inversion and integration operation and might not be suitable for the DOA rapid changing scenarios.…”

Section: In Intelligent Transportation Systems Like High Speed Railmentioning

confidence: 99%

See 1 more Smart Citation

A Fast Blocking Matrix Generating Algorithm for Generalized Sidelobe Canceller Beamformer in High Speed Rail Like Scenario

Dai

Abbasi

2021

IEEE Sensors J.

View full text Add to dashboard Cite

A fast algorithm to generate the Blocking Matrix for Generalized Sidelobe Canceller (GSC) beamforming is proposed in this paper. The proposed algorithm uses a Simplified Zero Placement Algorithm (SZPA) to directly generate the column vectors of the Blocking Matrix using the polynomial method. The constrained signal incoming angles are converted to spatial frequency and designated as zero locations in the Z domain. Independent vectors that span the whole left null space of the constraint matrix is then built using a simple shift operation. The algorithm also supports the derivative constraints used for robust beamforming. Compared to the conventional methods based on Singular Value Decomposition (SVD), the SZPA algorithm can generate Blocking Matrix more than 9 times faster for scenarios with 15 constraints and will be even more advantageous for more constraints. The Blocking Matrix generated by the SZPA and SVD methods is then implemented in the same GSC architecture for performance evaluation. The numerical simulation confirms that the same overall optimum state performance and learning speed can be achieved. By reducing the calculation time of blocking matrix from 1.541ms of SVD method to 0.168ms, the proposed SZPA algorithm is fast and insensitive to the number of constraints as the required calculation time incremental for each additional constraint with SZPA is only around 1/16 of SVD method. This makes it suitable for scenarios like train to infrastructure communication in High Speed Rail (HSR) where there are multiple constraints and frequent constraints update is required.

show abstract

Section: In Intelligent Transportation Systems Like High Speed Railmentioning

confidence: 99%

“…And this will consume one more degree of freedom as expected. Keep taking derivative over (21), it can be found that for higher order of derivatives, we can just put more zeros to the specified location. A simple simulation could illustrate the idea better.…”

Section: B Derivative Constraint Based Robust Beamformingmentioning

confidence: 99%

A Fast Blocking Matrix Generating Algorithm for Generalized Sidelobe Canceller Beamformer in High Speed Rail Like Scenario

Dai

Abbasi

2021

IEEE Sensors J.

View full text Add to dashboard Cite

show abstract

“…Moreover, it is known that, given the power spectrum, the autocorrelation sequence may be determined by taking the inverse discrete Fourier transform (IDFT) ofP (θ). However, from (25) it can be seen that the estimated power spectrum has two parts: the spatial power spectrum of the desired signal,P s (θ), and the noise-plus-interference section,P ipn (θ). Therefore, in order to compute the correlation sequence associated with the NPICM, it is need to find the IDFT of the noise-plus-interference section while zeroing the power spectrum in the direction of the SOI as follows…”

Section: B Proposed Rec-dft Approachmentioning

confidence: 99%

“…Furthermore, when coherent signals (with line spectra) occur, the Capon spatial spectrum's accuracy suffers severely while the performance of this method depends on ad-hoc parameters [24]. In order to avoid this problem, a very recent algorithm in [25] was proposed based on the reconstruction of the NPICM and DSCM. In this method, all interference powers as well as the desired signal power are estimated using low complexity principle of maximum entropy power spectrum.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Beamforming Based on Low-Complexity Discrete Fourier Transform Spatial Sampling

et al. 2021

Self Cite

View full text Add to dashboard Cite

In this paper, a novel and robust algorithm is proposed for adaptive beamforming based on the idea of reconstructing the autocorrelation sequence (ACS) of a random process from a set of measured data. This is obtained from the first column and the first row of the sample covariance matrix (SCM) after averaging along its diagonals. Then, the power spectrum of the correlation sequence is estimated using the discrete Fourier transform (DFT). The DFT coefficients corresponding to the angles within the noise-plusinterference region are used to reconstruct the noise-plus-interference covariance matrix (NPICM), while the desired signal covariance matrix (DSCM) is estimated by identifying and removing the noise-plusinterference component from the SCM. In particular, the spatial power spectrum of the estimated received signal is utilized to compute the correlation sequence corresponding to the noise-plus-interference in which the dominant DFT coefficient of the noise-plus-interference is captured. A key advantage of the proposed adaptive beamforming is that only little prior information is required. Specifically, an imprecise knowledge of the array geometry and of the angular sectors in which the interferences are located is needed. Simulation results demonstrate that compared with previous reconstruction-based beamformers, the proposed approach can achieve better overall performance in the case of multiple mismatches over a very large range of input signal-to-noise ratios.

show abstract

“…For each searching angle, we can calculate the DoP of the extracted approximate mainlobe interference in (8). As a kind of polarization rotation invariant, the DoP has a strong robustness in characterizing the polarization characteristics of the signal.…”

Section: Accurate Angle Estimation Of Interference Based On Dopmentioning

confidence: 99%

Multiple interferences suppression with space-polarization null-decoupling for polarimetrie array

Shi

et al. 2021

J. of Syst. Eng. Electron.

View full text Add to dashboard Cite

The adaptive digital beamforming technique in the space-polarization domain suppresses the interference with forming the coupling nulls of space and polarization domain. When there is the interference in mainlobe, it will cause serious mainlobe distortion, that the target detection suffers from. To overcome this problem and make radar cope with the complex multiple interferences scenarios, we propose a multiple mainlobe and/or sidelobe interferences suppression method for dual polarization array radar. Specifically, the proposed method consists of a signal preprocessing based on the proposed angle estimation with degree of polarization (DoP), and a filtering criterion based on the proposed linear constraint. The signal preprocessing provides the accurate estimated parameters of the interference, which contributes to the criterion for null-decoupling in the space-polarization domain of mainlobe. The proposed method can reduce the mainlobe distortion in the space-polarization domain while suppressing the multiple mainlobe and/or sidelobe interferences. The effectiveness of the proposed method is verified by simulations.

show abstract

Maximum Entropy-Based Interference-Plus-Noise Covariance Matrix Reconstruction for Robust Adaptive Beamforming

Cited by 52 publications

References 92 publications

A Fast Blocking Matrix Generating Algorithm for Generalized Sidelobe Canceller Beamformer in High Speed Rail Like Scenario

A Fast Blocking Matrix Generating Algorithm for Generalized Sidelobe Canceller Beamformer in High Speed Rail Like Scenario

Robust Adaptive Beamforming Based on Low-Complexity Discrete Fourier Transform Spatial Sampling

Multiple interferences suppression with space-polarization null-decoupling for polarimetrie array

Contact Info

Product

Resources

About