Distortionless space‐time adaptive processor based on MVDR beamformer for GNSS receiver

Dai, Xinzhi; Nie, Junwei; Chen, Feiqiang; Ou, Gang

doi:10.1049/iet-rsn.2017.0168

Cited by 36 publications

(49 citation statements)

References 14 publications

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“…The calculation method of Equation (13) can also be referred to Equations (9) and (10). Therefore, the array output can be denoted as the weighting summation of each sampled data tap as…”

Section: Array Modelmentioning

confidence: 99%

“…Unfortunately, although the antenna array processing can effectively suppress RFI, it will introduce Pseudo-Range (PR) bias and affect the positioning accuracy of GNSS receivers. For example, it is shown in [10] that the PR measurement deviation introduced by the array processing is in the order of 10 ns, which prevents the array processing being used in some high accuracy-requiring scenarios where the PR measurement deviation is usually suppressed to less than 1 ns, such as the guided missiles, measurement receivers, aircraft landing systems, and so on [11][12][13]. Therefore, it is important to study the influence of antenna array anti-jamming processing on PR measurements and its improvement [14].…”

Section: Introductionmentioning

confidence: 99%

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High Precision Pseudo-Range Measurement in GNSS Anti-Jamming Antenna Array Processing

Chen

Xie

et al. 2020

Electronics

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Radio frequency interference has become a rising problem to the signal of the Global Navigation Satellite System (GNSS). An effective way to achieve anti-jamming is by using an antenna array in GNSS signal processing. However, antenna array processing will cause a decline in the accuracy of pseudo-range measurements because of the channel mismatch and some other non-ideal factors. To solve this problem, space–time or space–frequency adaptive array processing is widely used for interference cancellation while constraining the delay of each antenna at the same time. In this paper, an anti-jamming algorithm with a time-delay constraint is proposed, where one antenna is chosen as the reference and data from other antennas is corrected based on the signal received from it. The deduction and simulation results show that the proposed algorithm can effectively improve the accuracy of pseudo-range measurements without degradation of anti-jamming performance.

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“…The calculation method of Equation (13) can also be referred to Equations (9) and (10). Therefore, the array output can be denoted as the weighting summation of each sampled data tap as…”

Section: Array Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

High Precision Pseudo-Range Measurement in GNSS Anti-Jamming Antenna Array Processing

Chen

Xie

et al. 2020

Electronics

Self Cite

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“…where w is the the space-time 2-D weight vector. Invoking MVDR beamformer [8], the optimal solution w MVDR of space-time 2-D weight vector can be expressed as…”

Section: Array Output Sinrmentioning

confidence: 99%

“…Therefore, the space-time adaptive antijamming method is developed to overcome the aforementioned problem, and several delay taps are placed behind each antenna element, namely, a temporal filtering is added on the basis of the spatial filtering. Thus, the space-time adaptive antijamming method can suppress more interference signals owing to the addition of temporal DOF [5][6][7][8][9][10]. A distortionless spacetime adaptive antijamming method is presented [5], which can not only obtain a higher DOF but also enhance the gain of GNSS signals.…”

Section: Introductionmentioning

confidence: 99%

“…Through the aforementioned processing, the twostage antijamming approach can significantly decrease distortion while maximizing signal-to-noise ratio (SNR). To achieve higher antijamming performance, a distortionless space-time adaptive processor based on minimum variance distortionless response (MVDR) beamformer is proposed [8]. It can maintain the linearity of space-time filter response, when odd number of delay taps is exploited.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Antijamming Based on Space-Time 2-D Sparse Array for GNSS Receivers

Du¹,

Liu²,

Tang³

et al. 2020

PIER M

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Space-time adaptive antijamming problem has received significant attention recently for global navigation satellite system (GNSS). It can jointly utilize spatial filters and temporal filters to suppress interference signals. However, most of the works on space-time antijamming problem presented in the literature require a space-time two-dimension (2-D) array with multiple antennas and delay taps. In this paper, an effective adaptive antijamming method based on a space-time 2-D sparse array is proposed. The maximum array gain is utilized to construct a space-time 2-D sparse array. The spacetime antijamming weight vector is given by minimizing the 2-D sparse array output power. Compared with the previous works, the presented method can have better antijamming performance than a spacetime 2-D uniform array. Simulation results verify the effectiveness and feasibility of the proposed method.

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Phase Compensation for Unconstrained GNSS Adaptive Array Processing

Chen

Lin

et al. 2019

Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery

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Distortionless space‐time adaptive processor based on MVDR beamformer for GNSS receiver

Cited by 36 publications

References 14 publications

High Precision Pseudo-Range Measurement in GNSS Anti-Jamming Antenna Array Processing

High Precision Pseudo-Range Measurement in GNSS Anti-Jamming Antenna Array Processing

Adaptive Antijamming Based on Space-Time 2-D Sparse Array for GNSS Receivers

Phase Compensation for Unconstrained GNSS Adaptive Array Processing

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