Faculty Publications
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Publications by NITK Faculty
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Item Systolic-Architecture-Based Matrix Multiplications and Its Realization for Multi-Sensor Bias Estimation Algorithms(Springer Science and Business Media Deutschland GmbH, 2021) Gopala Swamy, B.; Sripati Acharya, U.; Srihari, P.; Pardhasaradhi, B.The accelerators are gaining predominant attention in the HW/SW designs and embedded designs due to the less power consumption and parallel data processing capabilities compared to standard microprocessors and FPGA’s. In this paper, MSSKF (Multi-sensor Schmidt–Kalman filter)-based coupled bias estimation problem is considered for single target multiple sensors case. Here MSSKF augments the state vector and bias vector for bias estimation, results in computationally expensive as the dimensions of the state and sensors increases. Hence to address the computational complexity, digital signal processing (DSP) architectures are proposed and accelerated the algorithm to meet the real-time constraints. In the MSSKF algorithm, the overload of the algorithm is due to state covariance prediction and innovation covariance prediction. To realize the state covariance and innovation covariance, a folded DSP architecture and parallel processing based folded DSP architecture are proposed, respectively. The matrix multiplications are addressed with systolic arrays to gain the advantage of latency and parallel processing. Moreover, MSSKF using systolic array architectures simulated and synthesized in Vivado 2018.1 using Verilog and implemented on FPGA-Zynq-7000 board. The performance of the systolic-based accelerator realization was compared with normal matrix multiplication. © 2021, Springer Nature Singapore Pte Ltd.Item A Conceptual Framework for Knowledge Aided Passive Radar System(Institute of Electrical and Electronics Engineers Inc., 2021) Lingadevaru, P.; Srihari, P.; Pardhasaradhi, B.; Gunnery, S.Significant recent radar research has been focused on knowledge aided signal processing, waveform design, detection and target tracking applications. Passive radars have the edge over active radars in spectrum utilization and covert operation for target detection and tracking applications. Passive radars generally use the existing illuminators of opportunity to detect or track the targets. The knowledge pertaining to illuminator of opportunity (IOO) selection, spectrum sensing, and diversity technique can predominantly improve the received signal strength (RSS) at the passive radar receiver. This paper proposes a Conceptual framework to build a Knowledge Aided Passive Radar System (KA-PRS) based on spectrum sensing, IOO selection, and spatial diversity. The mathematical modelling and functional blocks to build the KA - PRS are discussed. The analytical and simulation results reveal that KA-PRS provides improved signal-to-noise (SNR) ratio compared with the traditional passive radar. © 2021 IEEE.Item High-Frequency and Low-Latency DSP Architecture for Information Matrix Fusion(Institute of Electrical and Electronics Engineers Inc., 2021) Praharshita, D.S.L.; Pardhasaradhi, B.; Srihari, P.; Shripathi Acharya, U.S.; Sharma, G.V.K.The centralized fusion architecture gives optimal global estimate by fusing all the measurements pertaining to a given target. The centralized architectures are computationally huge and requires full data rate requirements. Hence, in practice, decentralized architectures with Information matrix fusion (IMF) is popular to derive an estimate which is equal to optimal global estimate accomplished in centralized architecture. In this paper, a digital signal processing (DSP) architectural minimization technique of pipelining is applied to derive the highspeed IMF. We proposed two different DSP architectures, namely pipelined traditional IMF and pipelined adder-ladder IMF to reduce the critical path, which inturn, increases the architecture's operating frequency. Further, we derived an optimal number of pipeline stages and hardware resources that are required for a generalized N sensors case. The proposed pipelined adder-ladder IMF configuration requires a N + 1 pipeline stage and N + 2 pipeline stages for an even number of sensors and an odd number of sensors respectively. Besides that, The pipelined traditional IMF requires 2N + 1 stages to optimally pipeline and achieve the same operating frequency as that of pipelined adder-ladder IMF. Furthermore, the proposed pipelined adder-ladder IMF is superior in performance (less hardware and less latency) compared to pipelined traditional IMF. The theoretical analysis is performed with metrics (critical path, number of resources, and maximum achievable frequency) to compare various architectures presented in this research work. © 2021 IEEE.Item Quantized Directional Cosine measurements based Localization(Institute of Electrical and Electronics Engineers Inc., 2021) Reddy, B.B.N.; Gunnery, S.; Pardhasaradhi, B.; Srihari, P.Localization of target emitters using multiple simultaneous directional cosine (DC) measurements are popular and extremely useful in radar and sonar surveillance systems. Underwater localization, classification, and target tracking using hydrophone with limited bandwidth constraints is a challenging problem. In limited bandwidth applications, quantizing the measurements is an efficient way of representing measurements. The DC measurements are usually in the range of -1 to +1, the quantization of DC leads to inaccuracy in the estimated values. This paper presents the localization problem with quantized DC measurements in densely populated targets scenario. The localization achieved using two different estimation techniques: the least-squares (LS) triangulation and the Quasi newton (QN) method. Further, to explicitly study the quantization effect, we have used linear and optimal quantization techniques to quantize the DC measurements. The performance of the localization is quantified using the position root mean square error (PRMSE). © 2021 IEEE.Item Knowledge Aided Track Management: Multi-Target Tracking in the Presence of Electromagnetic Absorbers(Institute of Electrical and Electronics Engineers Inc., 2021) Srihari, P.; Dewangan, V.K.; Anvith, M.; Jayan, A.; Anurag, M.; Pardhasaradhi, B.Electromagnetic (EM) absorbers are used in the surveillance to inhibit the target reflections back to the EM sensor. In the presence of EM absorbers, the probability of detection (PD) of a target in a particular area is very low or zero. Hence, the traditional trackers report death (termination of an existing track) whenever the target enters the EM absorber zone. Similarly, the tracker reports as birth (initialization of new track) whenever the target comes out of the EM absorber zone. Hence, the continuous track appears as a track breakage due to the dead zone. This paper proposes an environment learning with previous knowledge of tracks, and accordingly track management rules are adapted. Based on the knowledge, whenever targets enters into dead zone, the tracker propagates the tracks throughout the dead zone based on the kinematics of the target. The proposed algorithm is demonstrated by using the Histogram probabilistic multi-hypothesis tracker (H-PMHT) owing to its performance and computational load. The simulation results reveal that the proposed knowledge aided track management provides a continuity in track in the presence of EM absorber. © 2021 IEEE.Item Stealthy GPS Spoofer Design by Incorporating Processing Time and Clock Offsets(Institute of Electrical and Electronics Engineers Inc., 2021) Pardhasaradhi, B.; Srihari, P.GPS receivers are ubiquitously present to provide position, navigation, and time (PNT) information for civilian and military applications. These GPS receivers can be misguided by intentional interference like jamming, meaconing, and spoofing. This paper presents efficient spoofer design by incorporating spoofer's processing time (spoofers receiver end to transmitter end processing delay), tracker processing time (delay due to state estimation), the difference in clock offsets (spoofer and target have different clock offsets) into account for generating spoofed measurements. These delays are incorporated in the spoofer's external delay to create a spoof measurement set. A spoofer with a target tracking module was proposed earlier without considering the significance of time delay information. The delay due to the tracker processing time has also been considered in this proposed spoofer design. The simulations are carried out for two test cases: the processing time delay and the difference in clock offset delay. Interactive multiple models (IMM) based dynamic state estimation filter is used to track the target (GPS receiver) of interest owing to its best performance compared with other filters. The proposed spoofer design outperforms the existing spoofer designs in position root mean square error (PRMSE). In addition to that, we also accomplished high performance of spoofing by increasing the number of spoofed satellite signals. © 2021 IEEE.Item Target Estimation Performance Improvement in Cooperative Radar and Communication system Spectrum Sharing(Institute of Electrical and Electronics Engineers Inc., 2021) Gunnery, S.; Pardhasaradhi, B.; Prashantha Kumar, H.; Srihari, P.This paper presents target estimation performance improvement in cooperative radar and communication system spectrum sharing system model. Due to cooperation, target returns results from the communication transmitter are also exploited to improve the target estimation performance. Further, Cramer-Rao Lower Bound (CRLB) is considered as a metric to evaluate the target estimation performance. In addition, the effect of transmitting energy and target reflection coefficient on CRLB is analyzed. The cooperative system model is compared with the non-cooperative radar and communication system spectrum sharing operation and stand-alone radar system operation. Results show that the cooperative radar and communication system spectrum sharing system model provides improved performance compared to non-cooperative and stand-alone operations. © 2021 IEEE.Item Analysis of 5G new radio waveform as an illuminator of opportunity for passive bistatic radar(Institute of Electrical and Electronics Engineers Inc., 2021) Lingadevaru, P.; Pardhasaradhi, B.; Srihari, P.; Sharma, G.V.K.Passive radar detects targets using the reflections of electromagnetic signals illuminated by unintended sources of opportunity in the given surveillance region. The illuminators of opportunity (IOO) like FM, DVB, DAB, LTE, WiMax, and radio frequency signals are used for the passive radar depending on the availability, frequency of operation and, type of application. This paper proposes the upcoming 5G New Radio waveform (5G NR) as an IOO for passive bistatic radar. The 5G NR waveform is used to perform parametric analysis of passive bistatic radar. The radar parameters like range resolution, velocity resolution, range product, maximum unambiguous PRF, and Cassini's ovals are investigated. Further, the 5G NR IOO is compared against existing LTE and other IOOs. Simulation results reveals that all the radar parameters are outperforming for the 5G NR waveform, claiming that 5G NR is a potential candidate for the future IOO. © 2021 IEEE.Item Intruder Detection and Tracking using 77GHz FMCW Radar and Camera Data(Institute of Electrical and Electronics Engineers Inc., 2022) Vandana, G.S.; Pardhasaradhi, B.; Srihari, P.Target detection and tracking using optical and radar sensors have many applications in surveillance. As the optical sensor helps to visualize the target and the radar can provide its range and velocity, their combination results in useful information for continuous monitoring and coherence. This paper presents a radar-camera experimental setup to detect and track intruders in a restricted area. A real-time experiment with different target speeds and various radar cross-sections(RCS) (1. A person running, 2. A cyclist, and 3. A motorcyclist). We deployed a 77GHz IWR1642BOOST FMCW (Frequency Modulated Continuous Wave) radar module as a radar unit and a phone camera with an aperture of f/1.79 as an optical sensor. The data collected from the radar and camera sensor are applied to detection and tracking modules to obtain target tracks. The radar provides the observations of range, Doppler, and angle information. These observations are used to estimate the state of the target via extended Kalman filtering(EKF), dBscan clustering, and global nearest neighbor(GNN) association, followed by track maintenance. The optical sensor provides video frames as input and output tracks via foreground detection, blob analysis, motion-based detection, Kalman filtering, and track maintenance. The experimental result shows that combining radar and optical sensors accomplishes tracking accuracy and coherence in target detection and tracking. © 2022 IEEE.Item An Experimental Evaluation of MIMO-SAR Imaging with FMCW Radar(Institute of Electrical and Electronics Engineers Inc., 2022) Sriharsha Nag, T.S.; Vandana, G.S.; Pardhasaradhi, B.; Srihari, P.Synthetic aperture radar (SAR) imaging is a widely used technique to generate two-dimensional and three-dimensional imaging based on the principle of moving sensors. This paper presents an experimental investigation of SAR imaging using an IWR6843ISK frequency modulated continuous waveform(FMCW) radar sensor on a moving platform and providing the stationary targets. In this experiment, the moving platform is used to recreate images with a higher spatial resolution based on a two-dimensional fast Fourier transform (2D-FFT) algorithm. Three different configurations are explored, namely: SAR, single input multiple output SAR (SIMO-SAR), and multiple input and multiple outputs SAR for imaging multiple targets within the vicinity. The real-time data is collected by moving the radar from 1-21m and observing two different stationary targets. The received data is processed using the 2D-FFT algorithm and obtaining the imaging for various configurations. The experimental results reveal that target detection is accomplished for all three configurations and comparable with ground truth. The MIMO-SAR outperforms and is a suitable candidate for automotive SAR imaging. © 2022 IEEE.