Millimetre Level Accuracy GNSS Positioning with the Blind Adaptive Beamforming Method in Interference Environments

Daneshmand, Saeed; Marathe, Thyagaraja

doi:10.3390/s16111824

Cited by 13 publications

(10 citation statements)

References 22 publications

(27 reference statements)

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“…The compressed sensing theory points out that when the signal is compressible or sparse, it can be projected into a low dimensional space via a measurement matrix, and then a certain reconstruction algorithm is used to recover the signal. The compression observation of s can be expressed as [31]r = Φs +ñ = Φ +ñ = A +ñ (9) where A cs = Φ is × sensing matrix. The information vector can be reconstructed accurately from using the despread received datar i and the 1 norm optimization.…”

Section: Spoofing Detection and Suppressionmentioning

confidence: 99%

“…With the development of antijamming technology, a new generation of satellite navigation receivers has adopted a series of interference suppression measures, including the use of the Wavelet packet transform (WPT) [5], neural network cancellation [6], and the adaptive notch filter [7,8] to suppress narrowband interferences, but these methods are not suitable for wideband interference suppression. Many antijamming receivers make use of the antenna array power inversion (PI) [9,10] algorithm to nullify the wideband interference or the adaptive beamforming algorithm to improve the output signal-to-noise ratio (SNR) of the array by nullifying the interference directions while forming the useful GNSS signal directional beam [11]. However, the degrees of freedom of antennas are limited by the number of antenna elements, and the space-time adaptive processing (STAP) method increases the degrees of freedom without increasing the array elements.…”

Section: Introductionmentioning

confidence: 99%

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A Combined Antijamming and Antispoofing Algorithm for GPS Arrays

Yang

Zhang

Tang

et al. 2019

International Journal of Antennas and Propagation

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The Global Positioning System (GPS), with its accurate positioning and timing information, has become a commonly used navigation instrument for many applications. However, it is susceptible to intentional interference such as jamming and spoofing. The conventional antijamming GPS receiver fails to work in a combined jamming and spoofing attack scenario. To solve the problem, a combined antijamming and antispoofing algorithm for a GPS receiver based on an antenna array is proposed. In this method, the jamming is eliminated by subspace projection, and then a compressed sensing framework is adopted to obtain the direction of arrival (DOA) of the despreading satellite navigation signal and detect the spoofing signal. According to the DOA of the authentic and spoofing signals, the receiver uses adaptive multibeamforming to concurrently achieve the undistorted reception of the authentic satellite signal and the suppression of the spoofing. We analyse three aspects of algorithmic performance: the antenna array direction diagram, the spoofing detection and the acquisition results. The simulation results and their analysis preliminarily show that the proposed method can detect and suppress GPS jamming and spoofing effectively.

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Section: Spoofing Detection and Suppressionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Combined Antijamming and Antispoofing Algorithm for GPS Arrays

Yang

Zhang

Tang

et al. 2019

International Journal of Antennas and Propagation

View full text Add to dashboard Cite

show abstract

“…Adaptive beamforming, which can enhance the signal of interest (SOI) while suppressing interferences automatically, is a data-dependent method and is widely applied in the fields of array signal processing, including radar, sonar, and wireless communication, etc. [1][2][3][4]. The standard Capon beamforming is one of the well-known types, which can achieve the optimum output signal-to-interference-plus-noise ratio (SINR) under ideal conditions without any model mismatches.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Beamforming with Optimal Covariance Matrix Estimation in the Presence of Gain-Phase Errors

Yao

Xin

et al. 2020

Sensors

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An adaptive beamformer is sensitive to model mismatch, especially when the desired signal exists in the training samples. Focusing on the problem, this paper proposed a novel adaptive beamformer based on the interference-plus-noise covariance (INC) matrix reconstruction method, which is robust with gain-phase errors for uniform or sparse linear array. In this beamformer, the INC matrix is reconstructed by the estimated steering vector (SV) and the corresponding individual powers of the interference signals, as well as noise power. Firstly, a gain-phase errors model of the sensors is deduced based on the first-order Taylor series expansion. Secondly, sensor gain-phase errors, the directions of the interferences, and the desired signal can be accurately estimated by using an alternating descent method. Thirdly, the interferences and noise powers are estimated by solving a quadratic optimization problem. To reduce the computational complexity, we derive the closed-form solutions of the second and third steps with compressive sensing and total least squares methods. Simulation results and measured data demonstrate that the performance of the proposed beamformer is always close to the optimum, and outperforms other tested methods in the case of gain-phase errors.

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“…Although the spread-spectrum processing gains vary from 30 to 40 dB, high interference signal ratio (ISR) interference with still cause significant positioning errors or paralysis on BDS receivers. Generally, there are several approaches to mitigate the interferences: time domain [ 1 , 2 , 3 , 4 ], frequency domain [ 5 , 6 , 7 ] and space domain [ 8 , 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

A BDS Interference Suppression Technique Based on Linear Phase Adaptive IIR Notch Filters

Zhao

Sun

et al. 2018

Sensors

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The continuous wave interferences (CWIs) and the narrow-band interferences (NBIs) have significantly impacted the acquisition, tracking and positioning accuracy of Beidou Navigation Satellite System (BDS) receivers. As an interference suppression technology with a simple structure and low hardware cost, the adaptive infinite-duration impulse response (IIR) notch filter has been widely employed in the receivers to mitigate the CWIs and the NBIs. However, the nonlinear phase characteristics introduced by the IIR notch filters into the navigation receivers, may cause the distortion of navigation signals. It also leads to amplitude and phase distortion of the correlation peak in acquisition and loop tracking, which consequently brings on positioning errors in the measurement domain. This problem, however, has been ignored by many previous papers. Meanwhile, some other researchers came up with the idea of equalizers and all-pass networks compensating the distortion, which is also highly infeasible. Therefore, we propose a new method of an adaptive linear phase IIR notch filter with low hardware cost which is composed of three parts—the complex IIR notch filters, the IIR linear phase structure, and the adaptive and variable step-size algorithms. Applying this method, interference suppression and the correlation peak distortion compensation can be achieved with a modest increase hardware cost. This paper compares the performance of the new method with other IIR filters in both CWI and NBI scene and presents the effects of its parameters on the anti-jamming performance. Simulation results show that the proposed module has better anti-jamming performance in NBI scene and can compensate for the correlation peak distortion in the meantime.

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Millimetre Level Accuracy GNSS Positioning with the Blind Adaptive Beamforming Method in Interference Environments

Cited by 13 publications

References 22 publications

A Combined Antijamming and Antispoofing Algorithm for GPS Arrays

A Combined Antijamming and Antispoofing Algorithm for GPS Arrays

Robust Adaptive Beamforming with Optimal Covariance Matrix Estimation in the Presence of Gain-Phase Errors

A BDS Interference Suppression Technique Based on Linear Phase Adaptive IIR Notch Filters

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