Browsing by Author "Pardhasaradhi, B."

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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. Â© 2021 IEEE.
A GNSS Position Spoofing Mitigation Algorithm using Sparse Estimation
(Institute of Electrical and Electronics Engineers Inc., 2022) Pardhasaradhi, B.; Gunnery, G.; Mahipathi, A.C.; Srihari, P.; Cenkarmaddi, L.R.
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. Â© 2022 IEEE.
A Modified Strassen Algorithm based DSP Accelerated 3D Kalman Filter
(Institute of Electrical and Electronics Engineers Inc., 2023) Mohalia, V.; Srihari, P.; Reddy, S.; Reddy, G.H.; Pardhasaradhi, B.
The high-speed Kalman filter (KF) algorithms are essential for robotics, autonomous vehicle, target tracking, and other applications. The dimensions of the state vector and traditional matrix multiplication (complexity of order O(n3)) are the two main reasons for the computational time of the K F algorithm. Hence, a matrix multiplication accelerator module is needed to accelerate the KF algorithm for higher dimensions of the state vector. In this paper, modified Strassen matrix multiplication (complexity of order O(n2.80)) is utilized to increase the computational efficiency of the KF algorithm. The number of cycles is evaluated against the dimensions of the KF algorithm to illustrate the proposed methodology. After that, 2D-KF and 3D-KF algorithms targeted on DSP processor TMS320C6678 using C language to ensure real-time processing. The 3 D-K F with a state of nine consumes 19.962 ~ms, 30.47 ~ms, and 40.04 ~ms of time by employing the hybrid Strassen, Strassen, and conventional matrix multiplication. It is observed that the usage of hybrid Strassen takes only half of the time provided by conventional multiplications. Â© 2023 IEEE.
A Multiple Llyods Approach for LiDAR Point Cloud Quantization and Communication
(Institute of Electrical and Electronics Engineers Inc., 2023) Dayananda, B.N.; Achala, G.; Srihari, P.; Raju, M.K.; Vandana, G.S.; Pardhasaradhi, B.
The development and usage of drones and LiDARs have become common in forestry, archaeology, surveillance, and intruders in recent years. Even though both domains reached a very mature state, the usage, integration of LiDAR scanning from drones, security, and low bandwidth constraints are still fantasy. This paper proposed to use LiDAR on a drone to scan the area, quantize the point cloud, and communicate it to the ground station through free space communication. The purpose of open space communication rather than cloud-based solutions is to avoid related security threats. In addition, this paper uses Lloyds-based quantization to achieve optimality in the quantization scheme. Before transmitting the point cloud, it is proposed to quantize it in parallel optimal quantizers. As a result of the proposed quantizer model, we calculated the RMSE, bandwidth, and choice of communication module for this particular scenario. The quantization loss is shown in terms of RMSE, bandwidth, and channel capacity requirements depicted with some bits. RMSE value obtained in this work for the Lloyds quantization method is 0.899. The LiDAR point cloud data is transmitted to ground station with data rate of 21Mbps utilizing free space optical communication. Â© 2023 IEEE.
A Mutual Interference Mitigation Algorithm for Dense On-Road Automotive Radars Scenario
(Institute of Electrical and Electronics Engineers Inc., 2023) Kumuda, D.K.; Srihari, P.; Seshagiri, D.; Raju, M.K.; Pardhasaradhi, B.
The mmWave frequency modulated continuous wave (FMCW) radars are widely adopted in the automotive industry because they work in all weather conditions. Due to the increased on-road density of mmWave radars, the primary radar mounted on the ego vehicle faces mutual interference. The traditional detection scheme employs a one-dimension fast Fourier transform (FFT) followed by a constant false alarm rate (CFAR) on the intermediate frequency (IF) signal to get the target detections. In the case of mutual interference, the IF signals behavior is abnormal and leads to miss-detection and false detections within the traditional framework. We propose a weighted beat signal normalization algorithm on the intermediate frequency (IF) signal followed by a traditional detection scheme as a mutual interference mitigation mechanism. This methodology implementation is easy since it does not disturb any processing modules like the mixer, LPF, FFT, and CFAR blocks in the architecture. The results demonstrate that, the SINR increases by the proposed method thereby minimizing the probability of missing the target detection. Â© 2023 IEEE.
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.
Adult and Child Classification using Automotive Radar for In-cabin Monitoring
(Institute of Electrical and Electronics Engineers Inc., 2024) Sreekumar, S.; Shashank, S.K.; Srihari, P.; Vandana, G.S.; Pardhasaradhi, B.; Cenkarmaddi, L.R.
The awareness and decision-making about the unattended child or pet inside a car is one of the emerging features in autonomous vehicles as a precaution to prevent hot car death. The automotive radars can provide the Doppler and spatial information about in-cabin passengers. This paper proposes to extract the range-Doppler images from the IQ radar data and process them using CNNs to classify the passenger as an adult or child. The IWR1642 radar module is used to collect the passenger details in both space and time within the car. A novel CNN architecture is proposed by trading off the accuracy and lightweight characteristics of the network. The proposed architecture provides 97.74Â± 0.34 accuracy (with 18.32 MB size) compared to the denseNet201 of 99.13Â± 0.3 (with 71.3 MB size) accuracy. The proposed architecture is compared against the existing pre-trained models like InceptionNet, MobileNet, EfficientNet, NASNet, VGGNet, DenseNet, ResNet, and Xception regarding accuracy and size. Â© 2024 IEEE.
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. Â© 2022 IEEE.
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. Â© 2021 IEEE.
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. Â© 2024 IEEE.
Clipping and Hampel Filtering Algorithm to Mitigate Mutual Interference for Automotive Radars
(Institute of Electrical and Electronics Engineers Inc., 2023) Kumuda, D.K.; Srihari, P.; Seshagiri, D.; Rajesh Kumar, P.R.; Pardhasaradhi, B.
The frequency modulated continuous wave (FMCW) radars are widely adopted in the automotive industry to serve the emergency brake assistant (EBA) and automatic cruise control (ACC) functions. Nowadays, autonomous vehicles on-road density increasing and creating a problem of mutual interference. Due to this mutual interference, the structural properties like periodicity and amplitude of intermediate frequency (IF) signal varies and creates undeserved target detections. It is observed that, applying a one-dimension fast Fourier transform (FFT) on the intermediate frequency (IF) results in increased false alarms and missed detections. This paper process a clipping followed by a Hampel filtering on the IF signal to mitigate this mutual interference. Initially, the clipping framework chopoff the unwanted and abrupt amplitude information from the IF signal. The threshold of the clipper circuit is taken as the standard deviation of the acquired IF signal. Second, the Hampel filter was employed to identify the outliers in time-series data and replace them with more representative values. The Hampel is configured in a sliding window to calculate the median by providing the standard deviation of the acquired IF signal. This methodology implementation is easy and can be placed as an intermediate block between IF and FFT. The results demonstrate that the proposed methodology facilitating the good detection rate by decreasing the false alarm rate and missed detections. Â© 2023 IEEE.
Comprehensive Track Unswappinng for Improved Tracker Performance
(Institute of Electrical and Electronics Engineers Inc., 2025) Raghu, J.; Lingadevaru, T.L.; Pardhasaradhi, B.; Srihari, P.; Tharmarasa, R.; Kirubarajan, T.
In practical surveillance systems, multiple-target tracking can suffer from undesirable effects such as track breakages and track swaps. Track stitching or track segment association (TSA) algorithms have been proposed in the literature to stitch broken tracks deemed to have originated from the same target across time and to improve track continuity. Measurements from multiple neighboring targets may fall within the validation gates of one another, causing association errors that may eventually lead to not just track breaks but also track swaps. Therefore, TSA alone is insufficient to improve the overall tracker performance, as it considers only the broken tracks but not the continuous ones that might have swaps among themselves or with other broken tracks. To mitigate the effects of track swaps, this article proposes an algorithm that detects and resolves possible track swaps using kinematic and nonkinematic—classification and amplitude—information. Track swap detection involves identifying the most likely instant of track swap occurrence. Further, the proposed algorithm is extended to stitch broken track segments (as in the standard TSA) and those tracks that are algorithmically broken due to the detection of possible swaps. Simulation results demonstrate the effectiveness of the proposed algorithm in resolving track swaps and thereby improving track purity and the overall tracker performance. © 1965-2011 IEEE.
Cyber Attacking Active FMCW Radar Signal AoA Estimation Using Passive FMCW Radar for ADAS Applications
(Institute of Electrical and Electronics Engineers Inc., 2024) Prakash, A.S.; Vandana, S.G.; Nandagiri, A.; Srihari, P.; Pardhasaradhi, B.; Cenkarmaddi, L.R.
Millimeter-wave (mmWave) radars are a popular choice for Advanced Driver Assistant Systems (ADAS) that identify and track objects in the field of view. These mmWave radars (the primary radar on ego vehicles) are susceptible to interference signals from other mmWave radars (secondary radars on traffic participant vehicles) in the vicinity, which can result in false detection and tracking triggers. Knowing the interference signal's angle of arrival (AoA) is critical for locating the secondary radar source. This study discusses the experiments with AoA estimation of interference signals created by secondary radars when the primary radar is in a passive state. We performed a 3-dimensional Fast Fourier Transform (FFT) on the received I-Q data and used a range-angle heatmap image to determine the signal's spatial pattern. The 3D FFT (range FFT on time-domain ADC samples, velocity FFT on chirps, and angle FFT across antennas) calculates the AoA of the signals. In this experiment, the 77GHz IWR1642 primary radar is in passive mode, while the other 77GHz secondary radars (AWR1642 and AWR2944) are in active mode, providing an interference attack. We also tried with different ranges (2m, 3m, 5m, and 8m) and azimuths to determine the stealthiness of the attack. The AoA for passive radar is a good fit for identifying spurious sources/illuminators of opportunities, electronic counter-countermeasures (ECCM), source localization, knowledge-aided passive radar systems, and cognitive radar development. Â© 2024 IEEE.
Depth Information Fusion Using Radar-LiDAR-Camera Experimental Setup for ADAS Applications
(Institute of Electrical and Electronics Engineers Inc., 2024) Dayananda, N.B.; Srivastava, N.; Achala, G.; Nandagiri, A.; Srihari, P.; Pardhasaradhi, B.; Cenkarmaddi, L.R.
Improved scene perception makes the safe driving of automotive vehicles (AVs) feasible. The most common automotive sensors for AV perception for detection, classification, a nd t racking a re t he Light Detection And Ranging (LiDAR), radar, and camera sensors. The most reliable sensors for determining range are LiDAR and radar. In this research, we consider the referencing from the camera-based object recognition to fuse the LiDAR and radar point cloud data. To minimize any unintended effects from sensor orientation and sampling time, all three sensors are installed, calibrated, and time-aligned for this experiment. Subsequently, the obtained camera sensor data is subjected to object detection using a MobileNet-based deep neural network (DNN). The radar and LiDAR point cloud data are projected with the two-dimensional bounding box width, length, and height used for object recognition. Following that, the range information from the radar and LiDAR is retrieved and combined using a weighted average fusion algorithm. This experiment is run on the ROS platform, using AWR1642 radar sensor and RealSense LiDAR camera L515 sensor. The object detection from the camera and conducting fusion on the radar and LiDAR sensor is a potential algorithm for the Advanced Driver Assistant System (ADAS) emergency brake assistant (EBA) function. Â© 2024 IEEE.
Design of Barker-7 Radar Pulse Compressor Using DSP Architecture Minimization Techniques
(Institute of Electrical and Electronics Engineers Inc., 2024) Anoop, K.; Dayananda, B.N.; Achala, G.; Srihari, P.; Pardhasaradhi, B.; Cenkarmaddi, L.R.
Pulse compression algorithms play an important role in achieving better range resolution (RR) in automobile radar and ultrasonic sensors. The RR is the sensor's capacity to distinguish between two targets positioned in the same angular direction but at different distances. The Digital Signal Processing Architecture (DSPA) used in the pulse compressor is crucial for reaching high speeds or reducing hardware needs. This work presents two unique radar pulse compressor DSPAs for Barker-7 sequences, based on latency and area. One proposed design is the unfolding DSPA technology, which increases sample rate and speed. At the same time, another architecture, the folding DSPA approach, reduces hardware utilization and power consumption. The proposed DSPA design architectures are implemented and verified with the Artix-7 FPGA Kit. The unfolded Barker-7 pulse compressor increased the speed by 1.87 times as compared to the standard broadcasting Barker-7 realization, as demonstrated by the hardware implementation results. Folded Barker-7 architecture consumed 89% less power than existing Barker-7 broadcast architecture. The DSPAs proposed for the Barker-7 pulse compressor are ideal for ultrasonic, sonar, and radar applications that require high speed and low power. Â© 2024 IEEE.
Distributed Fusion of Optimally Quantized Local Tracker Estimates for Underwater Wireless Sensor Networks
(Institute of Electrical and Electronics Engineers Inc., 2022) Reddy, B.N.B.; Pardhasaradhi, B.; Gunnery, G.; Srihari, P.
Multi-sensor underwater surveillance has been a significant research problem for civilian and naval applications. Due to limited bandwidth considerations, the underwater wireless sensor networks (UWSNs) use measurement quantization to transmit information from individual sensors to the fusion center to perform centralized tracking/fusion. However, at the measurement level, quantization of azimuth information is complex due to its non-linear behavior. To address this problem, this paper proposes to perform the distributed tracking and quantizing the local estimates (state and covariance) to provide improved bandwidth and reduce computational load. The local tracker estimates the updated state and covariance of a target's time-varying dynamics in the given surveillance from the obtained measurements using extended Kalman filter (EKF) and global nearest neighbor (GNN) data association. The measurement model contains both detections of target and false alarms. This paper uses optimal quantization rather than linear quantization owing to its minimal bandwidth requirement. Once the quantized local tracks are obtained at the fusion center, these tracks are quantified using track-to-track association (T2TA) in the S-D assignment framework. The associated tracks are fused using correlation-free fusion algorithms like covariance intersect (CI), sampling covariance intersects (SCI), ellipsoidal intersect (EI), and arithmetic average (AA) algorithms to achieve the global track. The position root mean square error (PRMSE), bandwidth, and error ellipses are used to quantify the performance of the proposed framework. The simulation results show that the PRMSE of the optimally quantized fusion estimates yields good agreement with the unquantized method. Simulation results further reveals that, optimal quantization utilizes lower bandwidth compared to linear quantization. In addition, optimally quantized local estimates accomplishes promising covariance regions at the fusion center. © 2013 IEEE.
DoA Estimation for Micro and Nano UAV Targets using AWR2243 Cascaded Imaging Radar
(Institute of Electrical and Electronics Engineers Inc., 2022) Kavya, T.S.; Vandana, G.S.; Srihari, P.; Leelarani, V.; Pardhasaradhi, B.
Frequency-modulated continuous wave (FMCW) radars accurately estimate the target's position and velocity, but the angular resolution is inadequate. The low radar cross section (RCS) unmanned aerial vehicles (UAVs) like micro UAVs (0.01m2) and nano UAVs (0.001m2) pose a significant threat to sensitive military and civilian installations. The DoA of the low RCS targets helps in making stealthy countermeasures. In this paper, the DoA of nano and micro UAVs is experimented using Texas instruments AWR2243 cascaded imaging radar in conjunction with a digital signal processing evaluation module (DSP EVM). The data is received from all the available 16 receivers, then the subspace method of multiple signal classification (MUSIC) algorithm is applied to estimate the DoA of the low RCS UAvs in hovering mode. The ground truth of the UAVs is fixed at 10m range and 12 Â° azimuth from the center of the radar using engineering protractor. The average estimated DoA for nano and micro UAV s is 12.80Â° and 11.43Â°, respectively, for the ground truth DoA. The AWR2243 cascaded imaging radar provides superior performance and suitable candidate for the DoA estimation for micro and nano UAVs compared to existing AWR1642, IWR1642, and IWR6843 radars. Â© 2022 IEEE.
DSP Architectures of Covariance Intersection Fusion Algorithm for Automotive Sensor Fusion
(Institute of Electrical and Electronics Engineers Inc., 2023) Praharshita, D.S.L.; Achala, G.; Srihari, P.; Shripathi Acharya, U.S.; Pardhasaradhi, B.
The data fusion from sensors within the automotive vehicle is vital for improved accuracy and safety. The centralized and information matrix fusion (IMF) algorithms are famous for providing an optimal fusion estimate. However, the IMF is not viable in automotive sensor fusion applications due to the limited bandwidth and low hardware resources. Hence, distributed fusion technology is widely adopted in the automotive sensor applications to achieve high-speed and low-area realizations. This paper proposes three digital signal processing (DSP) architectures for covariance intersection (CI) fusion algorithm: Pipelined-traditional CI, adder-ladder CI, and pipelined adder-ladder CI. The proposed DSP architectures are evaluated with hardware resource consumption (multipliers, adders, and delays), maximum achievable frequency, and latency of the architecture. In addition, proposed CI algorithms for Digital Signal Processing (DSP) architectures are compared with IMF DSP architectures. The hardware resources and optimal pipeline stages required for CI with respect to N number of sensors are provided. The traditional pipeline algorithm requires N number of stages where as the proposed pipelined version of adder-ladder CI requires a N-1 pipeline stage with additional 7N-1 and 7N-3 delay elements for even and odd number of sensors to achieve the overall system operating frequency to an operation of multiplier. The proposed DSP architectures are suitable for automotive sensor fusion due to their high operating frequency and low hardware resources. Â© 2023 IEEE.
Experimental Evaluation of Various LFM Waveforms for FMCW Radar Applications
(Institute of Electrical and Electronics Engineers Inc., 2022) Bhargavi, R.; Kumar Adibhatla, A.; Srihari, P.; Sagar Krishna, S.; Pardhasaradhi, B.
Various waveforms like linear sawtooth frequency modulated waveform, segmented linear sawtooth frequency modulated waveform, linear triangular frequency modulated waveform, and segmented linear triangular frequency modulated waveform are generated and tested. A hardware evaluation module is constructed as a prototype with a TSW14J56EVM capture card, AFE7950EVM transceiver, horn antennas, low noise amplifiers, and Texas Instruments high-speed data converter (HSDC) pro software. The inphase (I) and quadrature-phase (Q) components of the waveform are excited at the transmitter end and received at the receiver end. Rigorous experimentation is carried out by varying the number of chips per frame (16 and 32), the center frequency (850MHz and 2450MHz), and bandwidth (100MHz and 200MHz) to evaluate the performance of the waveform. It is observed that the up-chirp LFM is superior to all other configurations by providing the received power of -52.77dB by configuring the setup with 2450MHz center frequency, 100MHz bandwidth, and 32 chirps per frame. Â© 2022 IEEE.
Feasibility of Adopting 6G Frequencies for Transmitter of Opportunity by Passive Radar
(Institute of Electrical and Electronics Engineers Inc., 2022) Lingadevaru, P.; Pardhasaradhi, B.; Srihari, P.
Targets are detected by passive radar by analysing the electromagnetic signal reflections from unintentional opportunistic signal transmitters in the surveillance area. The passive bistatic radar selects the opportunistic emitters, also known as illuminators of opportunity (IOO), depending on the available IOO signals, operating frequency, and the kind of application. Most commonly used IOOs by the passive radar are frequency modulated signal (FM), digital video broadcasting signal (DVB), and radio frequency signals. Recent work suggests that the 5G New Radio (5G NR) waveform might provide an useful IOO for passive bistatic radar. In this analytical study we aim to carry out feasibility of adopting proposed 6G frequencies for IOO in a passive radar. Radar metrics such as range resolution, velocity resolution, range product, and Ovals of Cassini are examined. Furthermore, the 6G frequency bands are compared with existing IOOs. The simulation findings show that all of the radar parameters outperform for the 6G bands, implying that 6G is a viable alternative for future IOO. Â© 2022 IEEE.