Combining DCQGMP-Based Sparse Decomposition and MPDR Beamformer for Multi-Type Interferences Mitigation for GNSS ReceiversReport as inadecuate


Combining DCQGMP-Based Sparse Decomposition and MPDR Beamformer for Multi-Type Interferences Mitigation for GNSS Receivers


Combining DCQGMP-Based Sparse Decomposition and MPDR Beamformer for Multi-Type Interferences Mitigation for GNSS Receivers - Download this document for free, or read online. Document in PDF available to download.

College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China





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Academic Editor: Vittorio M. N. Passaro

Abstract In the coexistence of multiple types of interfering signals, the performance of interference suppression methods based on time and frequency domains is degraded seriously, and the technique using an antenna array requires a large enough size and huge hardware costs. To combat multi-type interferences better for GNSS receivers, this paper proposes a cascaded multi-type interferences mitigation method combining improved double chain quantum genetic matching pursuit DCQGMP-based sparse decomposition and an MPDR beamformer. The key idea behind the proposed method is that the multiple types of interfering signals can be excised by taking advantage of their sparse features in different domains. In the first stage, the single-tone multi-tone and linear chirp interfering signals are canceled by sparse decomposition according to their sparsity in the over-complete dictionary. In order to improve the timeliness of matching pursuit MP-based sparse decomposition, a DCQGMP is introduced by combining an improved double chain quantum genetic algorithm DCQGA and the MP algorithm, and the DCQGMP algorithm is extended to handle the multi-channel signals according to the correlation among the signals in different channels. In the second stage, the minimum power distortionless response MPDR beamformer is utilized to nullify the residuary interferences e.g., wideband Gaussian noise interferences. Several simulation results show that the proposed method can not only improve the interference mitigation degree of freedom DoF of the array antenna, but also effectively deal with the interference arriving from the same direction with the GNSS signal, which can be sparse represented in the over-complete dictionary. Moreover, it does not bring serious distortions into the navigation signal. View Full-Text

Keywords: GNSS; multi-type interferences suppression; sparse decomposition; DCQGMP; MPDR GNSS; multi-type interferences suppression; sparse decomposition; DCQGMP; MPDR





Author: Qiang Guo and Liangang Qi *

Source: http://mdpi.com/



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