Two articles titled, “1. A GNSS Position Spoofing Mitigation Algorithm using Sparse Estimation and 2. Robust Positioning and Grubbs Outlier Test for Navigation in GPS Spoofing Environment,” have been accepted for publication in IEEE INDICON 2022.

  1. Bethi Pardhasaradhia, Gunnery Srinatha, Ashoka Chakravarthi Mahipathia, Pathipati Sriharia, and Linga Reddy Cenkeramaddi, “A GNSS Position Spoofing Mitigation Algorithm using Sparse Estimation,” has been accepted for publication in IEEE INDICON 2022.
  2. Bethi Pardhasaradhi, Purushottama Lingadevaru, Balarami Reddy BN, Pathipati Srihari, and Linga Reddy Cenkeramaddi, “Robust Positioning and Grubbs Outlier Test for Navigation in GPS Spoofing Environment,” has been accepted for publication in IEEE INDICON 2022.

Keywords:Global navigation satellite system, Satellites, Receivers, Mathematical models, Trajectory, Kalman filters, State estimation

Abstract:The Global Navigation Satellite Systems (GNSS) are widespread for providing Position, Velocity, and Time (PVT) information across the globe. The GNSS usually employs the Extended Kalman Filter (EKF) framework to estimate the PVT information of the receiver. The GNSS receivers PVT information is falsified by using a mimic GNSS signals is called a spoofing attack. This paper focuses mainly to combat the spoofing attack using sparse estimation theory. A generalized mathematical model is proposed for authentic and spoofed pseudoranges at the GNSS receiver. After that, a generalized pseudorange measurement model is presented by combining the authentic and spoofed pseudorange measurements. It is assumed that, only a part of satellite signals are spoofed. Further, the GNSS receiver’s state is estimated by mitigating the spoofed pseudoranges and it is formulated as a Least Absolute Shrinkage and Selection Operator (LASSO) optimization problem. The simulated results, compares the proposed LASSO based EKF algorithm with traditional EKF framework. It is observed that, the proposed algorithm suppresses the spoofing effect. Moreover, the Position Root Mean Square Error (PRMSE) of the proposed algorithm decreases by increasing the number of spoofed measurements.

More details: DOI: 10.1109/INDICON56171.2022.10039936

Keywords:Measurement,Navigation,Simulation,Kinematics,Position measurement, information filters, Robustness

Abstract:Global positioning system (GPS) is favored to provide the position, velocity, and time (PVT) details across the globe. This paper proposes an epoch-by-epoch robust positioning algorithm followed by the Grubbs outlier test to address the GPS spoofing problem. We propose to accept both authentic and spoofed GPS signals to compute the robust positions. The robust positioning considers all possible combinations of measurements and generates several position estimates, which contain actual position, spoof position, and biased positions. In this case, the positions evolved due to spoof pseudorange measurements must be removed. Hence, we model eliminating spoof locations as an outlier problem and is addressed using Grubbs outlier test. The median of the processed data after the Grubbs test is the positional information at that epoch. Moreover, this problem is also extended to the Kalman filter’s (KF) framework to address the time-varying kinematics of the target. Simulations are carried out for various numbers of actual and spoofed pseudorange measurements. In order to illustrate the robustness of the proposed technique, position root mean square error (PRMSE) is taken as a metric.

More details:DOI: 10.1109/INDICON56171.2022.10039906

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