Current Issue : April - June Volume : 2013 Issue Number : 2 Articles : 5 Articles
A perceived emerging threat to GNSS receivers is posed by a spoofing transmitter that emulates authentic signals but with randomized\r\ncode phase and Doppler over a small range. Such spoofing signals can result in large navigational solution errors that are\r\npassed onto the unsuspecting user with potentially dire consequences. In this paper, a simple and readily implementable processing\r\nrule based on CNR estimates of the correlation peaks of the despread GNSS signals is developed expressly for reducing the\r\neffectiveness of such a spoofer threat. Consequently, a comprehensive statistical analysis is given to evaluate the effectiveness of the\r\nproposed technique in various LOS and NLOS environments. It is demonstrated that the proposed receiver processing is highly\r\neffective in both line-of-sight and multipath propagation conditions....
A threat to GNSS receivers is posed by a spoofing transmitter that emulates authentic signals but with randomized code phase and\r\nDoppler values over a small range. Such spoofing signals can result in large navigational solution errors that are passed onto the\r\nunsuspecting user with potentially dire consequences. An effective spoofing detection technique is developed in this paper, based\r\non signal power measurements and that can be readily applied to present consumer grade GNSS receivers with minimal firmware\r\nchanges. An extensive statistical analysis is carried out based on formulating a multihypothesis detection problem. Expressions\r\nare developed to devise a set of thresholds required for signal detection and identification. The detection processing methods\r\ndeveloped are further manipulated to exploit incidental antenna motion arising from user interaction with a GNSS handheld\r\nreceiver to further enhance the detection performance of the proposed algorithm. The statistical analysis supports the effectiveness\r\nof the proposed spoofing detection technique under various multipath conditions...
This paper studies Bayesian filtering techniques applied to the design of advanced delay tracking loops in GNSS receivers with\r\nmultipath mitigation capabilities. The analysis includes tradeoff among realistic propagation channel models and the use of a\r\nrealistic simulation framework. After establishing the mathematical framework for the design and analysis of tracking loops in the\r\ncontext of GNSS receivers, we propose a filtering technique that implements Rao-Blackwellization of linear states and a particle\r\nfilter for the nonlinear partition and compare it to traditional delay lock loop/phase lock loop-based schemes....
We address the indoor tracking problem by combining an Impulse Radio-Ultra-Wideband handset with an ankle-mounted Inertial\r\nMeasurement Unit embedding an accelerometer and a gyroscope. The latter unit makes possible the detection of the stance phases\r\nto overcome velocity drifts. Regarding radiolocation, a time-of-arrival estimator adapted to energy-based receivers is applied to\r\nmitigate the effects of densemultipath profiles. A novel quality factor associated with this estimator is also provided as a function of\r\nthe received signal-to-noise ratio, enabling us to identify outliers corresponding to obstructed radio links and to scale the covariance\r\nmatrix of radiolocation measurements. Finally, both radio and inertial subsystems are loosely-coupled into one single navigation\r\nsolution relying on a specific extended Kalman filter. In the proposed fusion strategy, processed inertial data control the filter\r\nstate prediction whereas Combined Time Differences Of Arrival are formed as input observations. These combinations offer low\r\ncomputational complexity as well as a unique filter structure over time, even after removing outliers. Experimental results obtained\r\nin a representatively harsh indoor environment emphasize the complementarity of the two technologies and the relevance of the\r\nchosen fusion method while operating with low-cost, noncollocated, asynchronous, and heterogeneous sensors....
The procedure of determining the initial values of the attitude angles (pitch, roll, and heading) is known as the alignment. Also, it\r\nis essential to align an inertial system before the start of navigation. Unless the inertial system is not aligned with the vehicle,\r\nthe information provided by MEMS (microelectromechanical system) sensors is not useful for navigating the vehicle. At the\r\nmomentMEMSgyroscopes have poor characteristics and it�s necessary to develop specific algorithms in order to obtain the attitude\r\ninformation of the object. Most of the standard algorithms for the attitude estimation are not suitable when using MEMS inertial\r\nsensors. The wavelet technique, the Kalman filter, and the quaternion are not new in navigation data processing. But the joint use\r\nof those techniques for MEMS sensor data processing can give some new results. In this paper the performance of a developed\r\nalgorithm for the attitude estimation using MEMS IMU (inertial measurement unit) is tested. The obtained results are compared\r\nwith the attitude output of another commercial GPS/IMU device by Xsens. The impact of MEMS sensor measurement noises on\r\nan alignment process is analysed. Some recommendations for the Kalman filter algorithm tuning to decrease standard deviation\r\nof the attitude estimation are given....
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