Faculty Publications
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Publications by NITK Faculty
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Item 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.Item Performance Analysis of Spectrum Sharing Radar in Multipath Environment(Institute of Electrical and Electronics Engineers Inc., 2023) Gunnery, G.; Pardhasaradhi, B.; Mahipathi, A.C.; Prashantha Kumar, P.K.; Srihari, P.; Cenkarmaddi, L.R.Radar based sensing and communication systems sharing a common spectrum have become a potential research problem in recent years due to spectrum scarcity. The spectrum sharing radar (SSR) is a new technology that uses the total available bandwidth (BW) for both radar based sensing and communication. Unlike traditional radar, the SSR divides the total available BW into radar-only and mixed-use bands. In a radar-only band, only radar sensor signals can be transmitted and received. In contrast, radar and communication signals can both be transmitted and received in the mixed-use band. Taking such BW sharing into account, this paper investigates the performance of SSR in an information-theoretic sense. To evaluate performance, mutual information (MI), spectral efficiency (SE) and capacity (C) metrics are used. Initially, this paper considered a clean environment (no multipath) in order to evaluate performance metrics in the mixed-use band with and without successive interference cancellation. Following that, this paper addresses the performance of BW allocation by allocating low to high BW in mixed-band. Furthermore, the performance metrics are extended to account for the multipath environment, and the same analogy as in a clean environment is used. In addition, the MI and SE of traditional radar system is taken into account when comparing the performance of SSR with and without the use of the SIC. Finally, MI and capacity results show that using the SIC scheme in a mixed-use band yields performance comparable to traditional radar and communication system. In terms of SE, the SSR with SIC scheme outperforms traditional radar and communication system. © 2020 IEEE.Item 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.Item A Survey on Waveform Design for Radar-Communication Convergence(Institute of Electrical and Electronics Engineers Inc., 2024) Chakravarthi Mahipathi, A.; Pardhasaradhi, B.; Lingadevaru, P.; Srihari, P.; D'Souza, J.; Cenkarmaddi, L.R.To provide service to an abundant number of communication users and to avoid the spectrum scarcity problem, many researchers are fascinated to work towards the convergence of radar sensing and communication systems. In addition, future intelligent systems like autonomous vehicles, Vehicle-to-everything (V2X), Unmanned Aerial Vehicles (UAV), and all smart systems are going to implement both radar and communication systems on the same platform, which motivates the researchers to focus on the development of Joint Radar-Communication Systems (JRCS). Cooperative Radar-Communication System (CRCS) and Dual Functional Radar Communication (DFRC) systems provide an opportunity for communication users to utilize radar resources without disturbing radar operation. Waveform design is essential in the development of new models and designs related to joint radar-sensing and communication systems. A cooperative radar communication system uses separate waveforms for radar and communication systems. The DFRC system uses the same waveform for radar and communication operations. So to model both joint radar communication systems one should have a clear idea regarding waveform design and its approaches. Therefore, this review paper focused on different waveform design approaches for modeling CRCS and DFRC systems. In addition, the prime objective of this review paper is to give a detailed view of the existing cooperative and dual-function waveform design approaches and provide a kick-start for new learners to work on this area. © 2023 IEEE.