Faculty Publications
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Publications by NITK Faculty
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Item Automotive Radar Signal Authentication via Correlation and Power Spectral Density(Institute of Electrical and Electronics Engineers Inc., 2024) Vishnu Prasad, P.; Vandana, G.S.; Nandagiri, A.; Srihari, P.; Pardhasaradhi, B.; Cenkarmaddi, L.R.Because of their comprehensive target detection, classification, and tracking capabilities, mm-wave radars are becoming increasingly popular in advanced driver assistance systems (ADAS). Unfortunately, these radars are vulnerable to attacks such as jamming and spoofing. This research presents a simple and low-cost radar signal authentication method that can be used in automotive radar receivers that lack external hardware or networking systems. The proposed technique of detecting correlation and power spectral density (PSD) classifies incoming signals as interference-free or not, and it may be swiftly implemented via a firmware update. As an example, the Texas Instruments (TI) IWR1642 frequency modulated continuous wave (FMCW) radar is tested in both non-jamming and jamming situations. The return signals are processed to get the correlation and power spectral density (PSD) observations and thereby classify the signals. © 2024 IEEE.Item GNSS Spoofing Detection and Mitigation in Multireceiver Configuration via Tracklets and Spoofer Localization(Institute of Electrical and Electronics Engineers Inc., 2022) Pardhasaradhi, B.; Gunnery, G.; Vandana, G.S.; Srihari, P.; Aparna., P.Global navigation satellite systems (GNSS) sensors estimate its position, velocity, and time (PVT) using pseudorange measurements. When there is no interference, the pseudoranges are due to authentic satellites, and the bearings is distinguishable. Whereas, in the presence of any intentional interference source like spoofer, the pseudorange measurements owing to spurious signals and all the bearings from the same direction. These spurious attacks yield either no position or falsified position to the GNSS receiver. This paper proposes to install multiple GNSS receivers on a vehicle (assumed to be cooperative) to detect and mitigate the spoofing attack. While installing multiple GNSS receivers, we assume that each GNSS receiver's relative position vector (RPV) is assumed to be known to other GNSS receivers. The installed GNSS receivers use the extended Kalman filter (EKF) framework to estimate their PVT. We proposed to calculate the equivalent-measurement and equivalent-measurement covariance of each GNSS receiver in the Cartesian coordinates in the tracklet framework. These tracklets are translated to the vehicle center using RPV to obtain translated-Tracklets. The translated tracklet based generalized likelihood ratio test (GLRT) is derived to detect the spoofing attack at a given epoch. In addition to that, these translated-Tracklets are processed in a batch least square (LS) framework to obtain the vehicle position. Once the attack is detected at a specific epoch, it quantifies that the position information is false. Moreover, another spoofing test is also formulated using DOA of signals. Once both the tests confirm the spoofing attack, the spoofer localization is performed using pseudo-updated states of GNSS receivers and acquired bearings in the iterative least-squares (ILS) framework. Mitigation of spoofing attack can be achieved either by projecting a null beam in the direction of the spoofer or by launching a counter-Attack on the spoofer. The simulation results demonstrate that the proposed algorithm detects spoofing attacks and ensures continuity in the navigation track. As the number of satellite signals increases, the algorithms provide better position root mean square error (PRMSE) for GNSS receivers track, vehicle track, and spoofer localization. © 2013 IEEE.Item Sequential Fusion Based Approach for Estimating Range Gate Pull-Off Parameter in a Networked Radar System: An ECCM Algorithm(Institute of Electrical and Electronics Engineers Inc., 2022) Lingadevaru, P.; Pardhasaradhi, B.; Srihari, P.Networked radar is an emerging and effective alternative to traditional radar systems to provide improved performance by fusing information from multiple radars. Further, networked radar systems (NRS) have found numerous deployments in military and civilian infrastructures in recent years. Electronic countermeasures (ECM) like jamming, Range Gate Pull-Off (RGPO), and Velocity Gate Pull-Off (VGPO) generally pose a high risk to the radar systems by injecting intentional interference. This paper proposes networked radar to detect the RGPO ECM attack and estimate the range gate deception parameter of the deceived local track in an NRS. Each radar comprises a local tracker to provide the local estimates (updated state and updated covariance), and these estimates are then sent to the fusion node. Thereafter, a track-to-track association (T2TA) is formulated at the fusion node to detect the deceived tracks using all the available local tracks. For the deceived track, the pseudo-measurements are created using the inverse Kalman filter-based tracklets. All the local tracks except deceived track are compensated and sequentially fused to create a reference measurement. After that, the deception parameter of the deceived track is estimated by using pseudo-measurement and the reference measurement by employing the recursive least square estimator (RLSE). In addition, the proposed algorithm is analyzed for single and multiple RGPO based ECM scenarios. Further, the Cramer Rao Lower Bound (CRLB) for the proposed methodology is derived. The results are quantified with a Position Root Mean Square Error (PRMSE), CRLB, innovation test, normalized estimation error squared (NEES) test, and confidence interval. The simulation results demonstrate that the proposed estimation technique provides good performance in the presence of all the local tracks are being attacked by RGPO ECM. Besides, it is evident from the results that estimator efficiency is falling below the 5% tail probability of the chi-square distribution. © 2013 IEEE.Item Multitarget Detection and Tracking by Mitigating Spot Jammer Attack in 77-GHz mm-Wave Radars: An Experimental Evaluation(Institute of Electrical and Electronics Engineers Inc., 2023) Kumuda, D.K.; Vandana, G.S.; Pardhasaradhi, B.; Raghavendra, B.S.; Srihari, P.; Cenkarmaddi, L.R.Small form factor radar sensors at millimeter wavelengths find numerous applications in the industrial and automotive sectors. These radar sensors provide improved range resolution, good angular resolution, and enhanced Doppler resolution for short range and ultrashort ranges. However, it is challenging to detect and track the targets accurately when a radar is interfered by another radar. This article proposes an experimental evaluation of a 77-GHz IWR1642 radar sensor in the presence of a second 77-GHz AWR1642 radar sensor acting as a spot jammer. A real-time experiment is carried out by considering five different targets of various cross sections, such as a car, a larger size motorcycle, a smaller size motorcycle, a cyclist, and a pedestrian. The collected real-time data are processed by four different constant false alarm rate detectors, cell averaging (CA)-CFAR, ordered statistics (OS)-CFAR, greatest of CA (GOCA)-CFAR, and smallest of CA (SOCA)-CFAR. Following that, data from these detectors are fed into two different clustering algorithms (density-based spatial clustering of applications with noise (DBSCAN) and K-means), followed by the extended Kalman filter (EKF)-based tracker with global nearest neighbor (GNN) data association, which provide tracks of various targets with and without the presence of a jammer. Furthermore, four different metrics [tracks reported (TR), track segments (TSs), false tracks (FTs), and track loss (TL)] are used to evaluate the performance of various tracks generated for two clustering algorithms with four detection schemes. The experimental results show that the DBSCAN clustering algorithm outperforms the K-means clustering algorithm for many cases. © 2001-2012 IEEE.