Faculty Publications

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    Rough fuzzy joint probabilistic association fortracking multiple targets in the presence of ECM
    (Elsevier Ltd, 2018) Satapathi, G.S.; Srihari, P.
    A novel rough fuzzy joint probabilistic data association algorithm (RF-JPDA) is presented to improve the performance of multitarget tracking in the presence of clutter, electronic countermeasures (ECM) and false alarms. The possibility data association matrix is evaluated by applying upper and lower approximations of validated measurements which are obtained from the radar. Four case studies are taken to validate the proposed data association algorithm. The proposed technique performance has been compared with conventional joint probabilistic data association filter (JPDA), fuzzy clustering means (FCM), and fuzzy Genetic Algorithm (Fuzzy-GA) approaches. A hybrid data association approach is formulated and examined for multi-target tracking using intelligent technique. Further, it is evident from the experimental results that RF-JPDA approach is providing enhanced performance in terms of position root mean square error (RMSE), velocity RMSE and execution time for all cases. The average position and velocity RMSE of RF-JPDA are 42.3% and 16.98% less when compared to conventional JPDA. Thus accomplishing novel and effective multiple target tracking algorithm based on expert systems. © 2018 Elsevier Ltd
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    Coherent Radar Target Detection With In-Band Cyclostationary Wireless Interference
    (Institute of Electrical and Electronics Engineers Inc., 2022) Gunnery, G.; Kumar, H.P.; Srihari, P.; Tharmarasa, R.; Kirubarajan, T.
    Spectral congestion necessitates the in-band operation or the spectrum-sharing of legacy radar and communication systems. Since these systems operate in the same band in spectrum-sharing mode, they interfere with one another. To address this problem from the radar's perspective, this paper considers the coherent detection of target-reflected radar signals in the presence of interference from an in-band cyclostationary digital modulated wireless communication signal. Three different cases of target-reflected radar signals, namely, deterministic signals, signals with random phase, and completely random signals, are considered in this paper. The optimum detection rules are derived for these three cases and the corresponding receiver structures for the equalization of the interfering signal are presented. Sub-optimum detection structures are also derived with the assumption that the in-band interference is a white stationary time-invariant Gaussian process. Further, considering the equalization, modified CFAR receiver structures are also presented. By considering the mathematical models for cyclostationary or periodic in-band interference, the performances of the optimum, sub-optimum detectors, and modified CFAR detectors are quantified analytically in terms of detection probability and false alarm probability, and the resulting receiver operating characteristic (ROC) curves are analyzed as a function of the signal-to-interference ratio. It is demonstrated that improper equalization of the interfering signal significantly affects the performance of the optimum detector and this impact is analyzed in detail. As spectrum-sharing becomes more prevalent due to spectrum congestion, the proposed optimal, sub-optimal, and modified CFAR detection rules and receiver structures can be incorporated into existing systems with substantial savings. © 2013 IEEE.
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    Tracking of Radar Targets With In-Band Wireless Communication Interference in RadComm Spectrum Sharing
    (Institute of Electrical and Electronics Engineers Inc., 2022) Gunnery, G.; Pardhasaradhi, B.; Prashantha Kumar, P.; Srihari, P.
    Radar and communication system (RadComm) spectrum sharing has received considerable attention from the research community in recent years. This paper considers the distributed radars present in the surveillance region with multiple in-band wireless communication transmitters (IWCTs). A new measurement model is proposed by considering both radar returns and returns due to IWCTs. The tracking performance is evaluated using the global nearest neighbor (GNN) tracker with an extended Kalman filter (EKF) for the received measurement set. A single radar case is considered, where near geometry scenario (IWCTs are placed near the radar and target) and far-geometry scenario (IWCTs are placed far from the radar and target) are considered to evaluate the tracking performance. It is observed that a large number of tracks are resulted due to IWCTs, and identifying the actual target track is ambiguous in a single radar case. Therefore, in the second case, multiple radars are placed to investigate the problem comprehensively. The track-to-track association (T2TA) is performed to identify the true target track on multiple tracks produced owing to the presence of IWCTs and the resulting tracks from all radars pertaining to the true targets. Once the true target tracks from each radar are identified, using the T2TA, the track-to-track fusion (T2TF) is carried out to improve the estimates of the true target. The simulation results are quantified with position root mean square error (PRMSE). The posterior Cramer-Rao lower bounds (PCRLBs) quantifying the achievable estimation accuracies are also presented. The simulation results reveal that the association and fusion of tracks from multiple radars identify the true target track with good accuracy and overcome the inability to determine the true track, as in the case of a single radar. Further, the results disclose that, as the number of radars increases, the T2TA and fusion improved the PRMSE. © 2022 IEEE.
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    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.
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    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.
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    Optimum Waveform Selection for Target State Estimation in the Joint Radar-Communication System
    (Institute of Electrical and Electronics Engineers Inc., 2024) Mahipathi, A.C.; Pardhasaradhi, B.P.; Gunnery, S.; Srihari, P.; D'Souza, J.; Jena, P.
    The widespread usage of the Radio Frequency (RF) spectrum for wireless and mobile communication systems generated a significant spectrum scarcity. The Joint Radar-Communication System (JRCS) provides a framework to simultaneously utilize the allocated radar spectrum for sensing and communication purposes. Generally, a Successive Interference Cancellation (SIC) based receiver is applied to mitigate mutual interference in the JRCS configuration. However, this SIC receiver model introduces a communication residual component. In response to this issue, the article presents a novel measurement model based on communication residual components for various radar waveforms. The radar system's performance within the JRCS framework is then evaluated using the Fisher Information Matrix (FIM). The radar waveforms considered in this investigation are rectangular pulse, triangular pulse, Gaussian pulse, Linear Frequency Modulated (LFM) pulse, LFM-Gaussian pulse, and Non-Linear Frequency Modulated (NLFM) pulse. After that, the Kalman filter is deployed to estimate the target kinematics (range and range rate) of a single linearly moving target for different waveforms. Additionally, range and range rate estimation errors are quantified using the Root Mean Square Error (RMSE) metric. Furthermore, the Posterior Cramer-Rao Lower Bound (PCRLB) is derived to validate the estimation accuracy of various waveforms. The simulation results show that the range and range rate estimation errors are within the PCRLB limit at all time instants for all the designated waveforms. The results further reveal that the NLFM pulse waveform provides improved range and range rate error performance compared to all other waveforms. © 2020 IEEE.