Browsing by Author "Vandana, G.S."

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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.
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.
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.
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.
Enhanced Intruder Detection Using mmWave Radar: A Spatiotemporal Clustering Approach for Robust Human Detection
(Institute of Electrical and Electronics Engineers Inc., 2024) Shashank, S.K.; Sreekumar, S.; Manjith Srijan, M.; Srihari, P.; Vandana, G.S.; Pardhasaradhi, B.P.; Cenkarmaddi, L.R.
Intruder detection using mmWave radar presents significant challenges due to the variability in the number of detections across spatial and temporal domains. This variability complicates the clustering process, particularly when detections from different body parts, such as the head and gait, are spatially distant, leading to the potential fragmentation of clusters. To address these challenges, we propose an enhanced clustering methodology that integrates both spatial and temporal information. The approach modifies the traditional DBSCAN algorithm by introducing a delayed window accumulation technique. This technique allows the radar system to accumulate detections over a specified duration, ensuring that an adequate number of detections are gathered before initiating clustering. Additionally, our method considers the physical dimensions of the human body to merge clusters that may be incorrectly separated due to the spatial distribution of detections. We further refine this approach by implementing a modified agglomerative clustering algorithm that leverages both spatial and temporal data to enhance cluster stability. The proposed methods are evaluated against the standard DBSCAN algorithm, demonstrating superior performance in accurately identifying human intruders, even under challenging detection scenarios. Our findings suggest that incorporating a delayed window accumulation strategy and considering spatiotemporal data are critical for robust intruder detection using mmWave radar. Â© 2024 IEEE.
Experimental Study of 24GHz Sense2Gol Pulse Radar Sensor for Human Vital Sign Measurement
(Institute of Electrical and Electronics Engineers Inc., 2021) Srihari, P.; Vandana, G.S.
Noncontact sensor based vital sign measurement has gained predominant attention in recent years. Frequency Modulated Continuous Wave (FMCW) radar-based sensors are deployed for this purpose at millimetre (mm) wavelengths (typically, 60 GHz and 77 GHz) to obtain vital sign measurements for various applications. This paper proposes a 24GHz Sense2Gol radar sensor-based heart rate (HR) and breath rate (BR) measurement system. Real data is collected using experimental setup from 12 male subjects and 12 female subjects of various age groups (with average age of male subjects is 40.5 years and average age of female subjects is 37.4 years). The data from the I/Q channel of the Sense2Gol radar sensor is passed through a band-pass filter followed by evaluating fast Fourier transform (FFT) to determine the HR beat per minute (bpm). To estimate the BR the arc tangent demodulation, phase unwrapping, followed by band-pass filtering is performed. The FFT is carried out for the resultant signal. The practical results from this experiment reveals that the male subjects and female subjects have an average value (HR: 63.92 bpm for male,64.97 bpm for female; BR:17.38 bpm for male, 17.45 bpm for female) of HR and BR respectively for male and female candidates. Further, over all HR across all subjects (both male and female) is 64.44 and BR across all subjects is 17.41. This Sense2Gol pulse radar sensor is relatively inexpensive among other sensors of this class and the data can be transferred using micro controller and an IoT module to nearest health care centers. Â© 2021 IEEE.
FMCW Radar-Based Detection and Tracking of Drones Using DBSCAN Clustering and Extended Kalman Filter for Anti-Drone Defense Systems
(Institute of Electrical and Electronics Engineers Inc., 2024) Srihari, P.; Vandana, G.S.; Kumar, U.; Nandagiri, A.; Pardhasaradhi, B.P.; Cenkarmaddi, L.R.
This paper aims to develop a radar-based detection and tracking system to mitigate the threats posed by drones, particularly those carrying malicious payloads. Due to the limitations of cameras in adverse weather and the high costs of LiDAR systems, radar technology is employed as a cost-effective alternative. The system utilizes 3D FFT followed by CA-CFAR for drone range-azimuth detections. The range-azimuth detections are clustered using DBSCAN. We simplified the extended target tracking problem into point target tracking based on the drone's size, with the dBSCAN cluster center acting as the measurement for the tracker. The tracking algorithm combines an Extended Kalman Filter (EKF) with Global Nearest Neighbor (GNN) data association. Experiments were conducted using a 77 GHz AWR1642 radar sensor to track a micro drone of hexacopter type within a range of 10m to 100m. The results demonstrated effective tracking capabilities with radar sensors successfully generating tracks. This study highlights the viability of radar-based systems for anti-drone applications, offering a practical solution for enhancing infrastructure security against potential drone threats. Â© 2024 IEEE.
FMCW Radar-Based UAV Detection and Tracking Using Transfer Learning
(Institute of Electrical and Electronics Engineers Inc., 2024) Sreekumar, S.; Shashank, S.K.; Srihari, P.; Nandagiri, A.; Vandana, G.S.; Pardhasaradhi, B.P.; Cenkarmaddi, L.R.
This research investigation offers a novel method for monitoring and detecting unmanned aerial vehicles (UAVs) by combining transfer learning neural networks with Frequency Modulated Continuous Wave (FMCW) radar. The system utilizes a 60 GHz Texas Instruments IWR6843ISK radar with a DCA1000 board to capture raw radar signals, which are subsequently processed to generate range-angle heat maps. Ground truth data for UAV positioning is meticulously obtained using a dual GPS setup, where one GPS is stationed at the radar and the other is mounted on the UAV. The processed range-angle heat maps serve as the input for various transfer learning models, including DenseNet, InceptionV3, MobileNet, ResNet, and VGG, which are employed to compute the range data and angle data of the UAV. The results emphasize the potential of transfer learning in improving radar signal processing by demonstrating the effectiveness of these models in attaining accurate UAV detection and tracking. This approach is pivotal for applications requiring precise UAV monitoring, offering a robust solution for scenarios where traditional radar systems may fall short. The study underscores the advantages of leveraging transfer learning for improved radar-based UAV detection and sets the stage for future advancements in autonomous aerial monitoring and surveillance systems. Â© 2024 IEEE.
FPGA Implementation of Moving Target Indicator Filter for FMCW Radar Data
(Institute of Electrical and Electronics Engineers Inc., 2023) Sreelekha, N.; Vandana, G.S.; Srihari, P.; Leelarani, V.; Raju, M.K.; Sreenivasula Reddy, T.S.
This study examines several digital finite impulse response (FIR) filter approaches for moving target indication (MTI) employing short-range FMCW radar sensors. The FIR filters can filter out low doppler shift responses from undesirable stationary targets. A 77 GHz AWR1642 FMCW radar sensor and a DCA1000 data capture card are used to build a hardware configuration. A single data frame (samples Ã— chirps) containing a target approaching the radar is been considered. The recorded radar is preserved in a 256x64 matrix of in-phase and quadrature-phase components, which is then processed using various digital filters. The radar provides insights into doppler characteristics for the observations. This study proposes designing and implementing a two-tap and a three-tap FIR filter-based MTI processing module to reduce static targets. The VLSI DSP pipelining approach is deployed to improve filter performance regarding critical path delay and throughput. Â© 2023 IEEE.
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.
High Speed and Low Power DSP Architectures for Barker-13 Radar Pulse Compressor
(Institute of Electrical and Electronics Engineers Inc., 2022) Anoopkumar, K.A.; Pardhasaradhi, B.; Vandana, G.S.; Rajeswari, R.; Srihari, P.
This paper proposes two novel efficient DSP architectures for the Barker-13 sequence for radar coded waveform design. Firstly, the traditional pulse compressor architectures are modified by using unfolded DSP techniques to achieve higher sampling rates for high-speed applications. Secondly, the reduction in hardware utilization and power consumption are addressed by the folding technique. Further, the proposed architectures are implemented on Artex-7 Field Programmable Gate Arrays (FPGA). The hardware implementation results demonstrates that the unfolded pulse compressor increased the speed by 3.25 times compared to traditional broadcasting filter realization. On the other hand, the folded architecture reduced the power usage by 15.2% in comparison to broadcast architecture. These pulse compressors can be deployed for high speed and low power radar/sonar applications. Â© 2022 IEEE.
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. Â© 2022 IEEE.
Measurement and Evaluation of Human Vital Sign using 77GHz AWR1642 FMCW Radar Sensor
(Institute of Electrical and Electronics Engineers Inc., 2021) Srihari, P.; Vandana, G.S.; Raghavendra, B.S.
This paper proposes vital sign measurements of humans like heart rate (HR) and respiration rate (RR). The Texas Instruments AWR1642, frequency modulated continuous wave (FMCW) mmwave radar sensor, operating as 77-81 GHz frequency with 4GHz as the sweep bandwidth of the linear frequency modulated (LFM) waveform, is deployed to measure the HR and RR vital parameters. Here, twenty subjects (10 male; 10 female) experimental data has been collected using TI AWR1642 radar sensor, personal computer (PC), and DCA1000 data acquisition module. The HR and RR algorithm is applied to the process data to measure the HR and RR of these subjects. The male and female subjects' average HR is 78.587 and 77.827, respectively. Further, the average RR of the male and female subjects is 19.959 and 19.23, respectively. Furthermore, a pulse oximeter(POM) obtains HR ground truth information to validate the proposed method. The overall absolute mean error percentage(MEP) compared to pulse oximeter data is 4.7935% for 20 volunteers who have participated in the experiment. Â© 2021 IEEE.
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.
Real Time Vital Sign Monitoring System using AWR1642 Radar Module with Remote Access
(Institute of Electrical and Electronics Engineers Inc., 2022) Dayananda, B.N.; Vandana, G.S.; Srihari, P.; Pardhasaradhi, B.
The remote access to vital sign measurements like pulse rate (PR) and breathing rate (BR) of a patient to doctors and family members makes it much more helpful in patient risk analysis. Texas Instruments AWR1642 frequency modulated continuous wave (FMCW) radar operates at 77-81 GHz frequency with 4 GHz sweep bandwidth for linear frequency modulated (LFM) waveform. In the literature, AWR1642 is used to determine a person's PR and BR in an offline mode. In this paper, the AWR1642 radar module is integrated with Raspberry Pi 4 Model B (Pi4B), and a network connection is established using SIM7600G-H 4G HAT and accessed through TeamViewer software. For this experiment, we have considered ten males and ten females in the age group of 19-52 years and 18-29 years, respectively. The male and female attendees' average PR is 84.84bpm and 79.9965bpm, respectively. The male and female attendees' average BR is 18.408bpm and 16.526bpm, respectively. Ground truth data is gathered from a fingertip pulse oximeter(PO) to verify our readings of PR and BR. The overall absolute mean error (AME) of PR and BR compared to the PO data is 0.6430 % and 4.2595% for the 20 volunteers who participated in the experiment. Â© 2022 IEEE.
Real-time Radar Imaging with Time Domain Correlation and Doppler Beam Sharpening
(Institute of Electrical and Electronics Engineers Inc., 2024) Kumar, S.A.; Achala, G.; Vandana, G.S.; Srihari, P.; Pardhasaradhi, B.; Cenkarmaddi, L.R.
Imaging with radar serves numerous purposes across remote sensing, monitoring civil infrastructure, detecting passing vehicles, and recognizing vulnerable road users (VRUs) within Advanced Driver Assistance Systems (ADAS). In most ADAS applications, one among a variety of radars, the millimeter wave (mmWave) radars, are limited to acquiring range, azimuth, elevation, and Doppler information. Configuration of the mm-wave radar in imaging form by fully utilizing built-in sending and receiving models is proposed in the work presented in this paper. The mm-wave radar is placed on a mobile platform, and the time domain correlation (TDC) is applied, followed by Doppler beam sharpening (DBS), to obtain radar imaging. The proposed algorithm was demonstrated with the help of IWR1642 radar, and real-time experiments were conducted with targets like cars, bicycles, and bikes. The mm-wave radar equipment and platform were moved with an approximate velocity and acquired I-Q channel data, further processed with the TDC-DBS algorithm. The experimental findings demonstrate successful target detection across scenarios considered in our work. Notably, the MIMO configuration on a fast-moving platform, along with the TDC-DBS algorithm, yielded superior results compared to the TDC algorithm. This algorithm stands out as a promising choice for automotive industry applications, such as imaging guardrails, detecting passing vehicles, and identifying vulnerable road users using side-mounted radar configurations. Â© 2024 IEEE.
Real-Time UAV Altitude Estimation and Data Transmission via mmWave Radar and Edge Computing
(Institute of Electrical and Electronics Engineers Inc., 2024) Vandana, G.S.; Srihari, P.; Kumar, U.; Nandagiri, A.; Pardhasaradhi, B.P.; Cenkarmaddi, L.R.
This paper presents a novel approach for UAV altitude estimation and data transmission using a 60 GHz IWR6843 mmWave radar mounted on a micro-drone, coupled with a Raspberry Pi edge device. The radar, configured in a long-range mode, leverages its high accuracy in altitude measurement, surpassing the performance of traditional UAV altimeters. The radar altimeter data is processed on the Raspberry Pi and wirelessly transmitted to the cloud, from which it can be accessed by a ground station for real-time monitoring and analysis. To validate the accuracy of the radar-based altitude measurements, GPS data is simultaneously recorded on the UAV, serving as a ground truth reference. Experimental results demonstrate that the radar-based measurements closely match the GPS-derived altitudes, showcasing the effectiveness of the proposed system. This approach not only improves altitude estimation accuracy but also enhances the reliability of UAV operations in various environments. Potential applications of this system include precision agriculture, disaster management, and search and rescue operations, where accurate altitude data is critical for mission success. The integration of mmWave radar with edge computing and cloud-based data management opens new avenues for real-time UAV monitoring and autonomous navigation. Â© 2024 IEEE.
SAR Imaging with Automotive Radar: Range Migration Algorithm, Experiment, and Future Directions in Automotive Vehicle
(Institute of Electrical and Electronics Engineers Inc., 2022) Sriharsha Nag, T.S.; Vandana, G.S.; Pardhasaradhi, B.; Srihari, P.
Synthetic Aperture Radar (SAR) imaging with air-borne radar has many applications in remote sensing, surface mapping, and civil infrastructure monitoring. In contrast, the Millimeter wave (mmWave) radars are confined to the automotive industry to fetch information like range, azimuth, and elevation. In this paper, we proposed configuring the mm-wave radar in SAR mode to utilize the availability of multiple transmitters and receivers. The frequency modulated continuous wave (FMCW) radar is ported onto a moving platform, and a range migration algorithm (RMA) is performed to perform SAR imaging. The real-time experiment was conducted using IWR6843ISK radar and explored different configurations like SAR, single-input multiple-outputs SAR (SIMO-SAR), and multiple-input multiple-outputs SAR (MIMO-SAR). In addition to that, the platform movement is also considered by varying the speed from slow to high. The acquired I-Q data is processed using a range migration algorithm (RMA) by following the processing steps like a two-dimensional fast fourier transform (2D-FFT), Stolt interpolation, azimuth compression, and inverse FFT (IFFT). The experimental results reveal that the target detection is accomplished for all the cases. The best results can be obtained for MIMO configuration with a high-speed moving platform. These results can be highly applicable for the automotive industry to perform SAR imaging on SRR radars which are being deployed on the side of the vehicle to monitor the guard rails, crossing vehicles, and VRU. Â© 2022 IEEE.