Browsing by Author "Pirsiavash, Ali"
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- ItemOpen AccessCharacterization of Signal Quality Monitoring Techniques for Multipath Detection in GNSS Applications(2017-07-05) Pirsiavash, Ali; Broumandan, Ali; Lachapelle, GérardThe performance of Signal Quality Monitoring (SQM) techniques under different multipath scenarios is analyzed. First, SQM variation profiles are investigated as critical requirements in evaluating the theoretical performance of SQM metrics. The sensitivity and effectiveness of SQM approaches for multipath detection and mitigation are then defined and analyzed by comparing SQM profiles and multipath error envelopes for different discriminators. Analytical discussions includes two discriminator strategies, namely narrow and high resolution correlator techniques for BPSK(1), and BOC(1,1) signaling schemes. Data analysis is also carried out for static and kinematic scenarios to validate the SQM profiles and examine SQM performance in actual multipath environments. Results show that although SQM is sensitive to medium and long-delay multipath, its effectiveness in mitigating these ranges of multipath errors varies based on tracking strategy and signaling scheme. For short-delay multipath scenarios, the multipath effect on pseudorange measurements remains mostly undetected due to the low sensitivity of SQM metrics.
- ItemOpen AccessGNSS Code Multipath Mitigation by Cascading Measurement Monitoring Techniques(2018-06-19) Pirsiavash, Ali; Broumandan, Ali; Lachapelle, Gérard; O'Keefe, Kyle P. G.Various measurement monitoring techniques are investigated to mitigate the effect of global navigation satellite systems (GNSS) code multipath through error correction, stochastic weighting of measurements and detection and exclusion (or de-weighting) of affected measurements. Following a comprehensive review of each approach, the paper focuses on detection/exclusion and detection/de-weighting techniques where several single and dual-frequency monitoring metrics are employed in a combination with time-averaging and the M of N detection strategy. A new Geometry-Free (GF) detection metric is proposed given its capability to be combined with a preceding Code-Minus-Carrier (CMC)-based error correction to reduce the number of excluded or de-weighted measurements and thus preserve the measurement geometry. Three geometry-based algorithms, namely measurement subset testing, consecutive exclusion and iterative change of measurement weights are investigated to address multipath scenarios with multiple simultaneously affected measurements. Experimental results are provided using GPS L1, L2C and L5 data collected in multipath environments for static and kinematic scenarios. For GPS L1, the proposed combined method shows more than 38% improvement over a conventional Carrier-to-Noise-density ratio (C/N₀)-based Least-Squares (LS) solution in all but deep urban canyons. Lower performance was observed for L2C and L5 frequencies with a limited number of satellites in view.
- ItemOpen AccessGNSS Signal and Measurement Quality Monitoring for Multipath Detection and Mitigation(2019-08) Pirsiavash, AliReceiver level Global Navigation Satellite Systems (GNSS) Signal and Measurement Quality Monitoring (SQM and MQM) to detect and de-weight measurements distorted by multipath are investigated. SQM and MQM monitoring metrics are defined at the tracking and measurement levels of the receiver; a new geometry-based de-weighting technique is developed. Following an analytical discussion of the sensitivity and effectiveness of the metrics, field data analysis is provided for static and kinematic modes to verify practical performance. Results obtained for the designed SQM and MQM-based detection metrics show reliable performance of 3 to 5 m Minimum Detectable Multipath Error (MDME). Although limited by multipath characteristics and measurement geometry, when detected faulty measurements are de-weighted, positioning performance improves by up to 53% for different multipath scenarios.
- ItemOpen AccessReceiver-level Signal and Measurement Quality Monitoring for Reliable GNSS-based Navigation(2019-01-09) Pirsiavash, Ali; Lachapelle, Gerard Jules; O'Keefe, Kyle P. G.; Broumandan, Ali; Lichti, Derek D.; Gao, Yang; Lohan, Elena-SimonaGlobal Navigation Satellite Systems (GNSS) are widely used in everyday and safety of life services as the main system for positioning and timing solutions. Reliability and service integrity are of utmost importance given a variety of error sources and threats. In the case of aviation and maritime applications, system integrity includes ground and space-based augmentation systems. These externally-aided monitoring systems do not provide a satisfactory solution for land users due to the multiplicity of error sources in the user's local environment, such as multipath. This research investigates receiver level stand-alone integrity monitoring solutions for such users. The methodology is based on Signal and Measurement Quality Monitoring (SQM and MQM) to detect and exclude or de-weight faulty measurements, with multipath and spoofing being the major concerns. Different monitoring metrics are defined and investigated for multipath detection and new geometry-based exclusion and de-weighting techniques are developed. Following an analytical discussion of metric sensitivity and effectiveness, simulated and field data analysis are provided to verify practical performance. Results obtained for the designed SQM and MQM-based detection metrics show reliable performance of 3 to 5 m Minimum Detectable Multipath Error (MDME). Although limited by multipath characteristics and measurement geometry, when detected faulty measurements are excluded or de-weighted, positioning performance improves for various multipath scenarios. In order to effectively classify multipath and spoofing, a spoofing simulator is designed, implemented and tested for selected time and position spoofing scenarios. A new spoofing strategy is described to investigate the minimum number of satellite signals required for an effective spoofing attack. Results show that in an overlapped spoofing scenario, at least 60% of signals are spoofed and thus distorted. This rate of signal distortion is not the case in all but harsh multipath scenarios and is used to distinguish spoofing attacks from multipath. More importantly, it is shown that distortion of more than half of the signals makes position solutions unreliable regardless of the error source. For selected scenarios, two-dimensional time/frequency widely-spaced SQM metrics are also developed to detect spoofing signals with about 3% false alarm probability imposed by multipath and other sources of signal distortion.