Browsing by Author "Vandana, S.G."

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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.
MIMO-SAR Image Reconstruction Experiment Using Back-Projection Algorithm with Automotive Radar for ADAS Applications
(Institute of Electrical and Electronics Engineers Inc., 2024) Jena, P.; Singh, A.; Vandana, S.G.; Nandagiri, A.; Srihari, P.; Pardhasaradhi, B.; Cenkarmaddi, L.R.
Synthetic aperture radar (SAR) imaging has numerous uses in surface mapping, civil infrastructure, remote sensing, and terrain monitoring. Despite the benefits of multiple input multiple outputs (MIMO) in automotive radars, they are primarily used to provide range, azimuth, and elevation information for automotive applications. Obtaining acceptable angular resolution for automotive radar is a recurring difficulty due to vehicle-to-vehicle, vehicle-to-ground, vehicle-to-guardrail, and vehicle-to-tunnel discrimination. The purpose of this work is to demonstrate MIMO-SAR for finer angular resolution utilizing the 77-GHz Texas Instruments (TI) frequency-modulated continuous wave (FMCW) AWR1642 radar. SAR and MIMO radar topologies are used to increase synthetic or virtual aperture while maintaining adequate angular resolution. SAR is used to rebuild images from experimental data, and the images are created using a backpropagation algorithm. The findings are presented for SAR, MIMO, and MIMO-SAR. Furthermore, the experimental demonstration of MIMO-SAR using 77 GHz automobile radar verifies the prior modeling results. In addition, MIMO-SAR has been shown to provide better angular resolution than SAR and MIMO approaches. This algorithm's superior performance makes it appropriate for the automotive industry to perform SAR imaging on ego-corner deployed short-range radars (SRR) to picture guard rails, crossing vehicles, and VRUs. Â© 2024 IEEE.
MTI Filter DSP Architectures in FMCW radar Framework for ADAS Applications
(Institute of Electrical and Electronics Engineers Inc., 2023) Sreelekha, N.; Vandana, S.G.; Leelarani, V.; Srihari, P.; Pardhasaradhi, B.
The digital Finite Impulse Response (FIR) filter emerges as a highly promising solution for enhancing Moving Target Indication (MTI) capabilities, particularly within the short-range Frequency-Modulated Continuous-Wave (FMCW) Radar framework. FIR filters prove instrumental in effectively filtering out low Doppler shift responses originating from stationary targets, thus improving radar performance in detecting moving objects. Milli-meter-wave Radar sensor AWR1642 of 77 GHz from Texas Instruments and a DCA1000 EVM capture card are used to record real-time data with moving target, which is then processed using high-speed data converter pro (HSDC) software focusing on the detection and tracking of moving targets. The frames of complex data from radar processing through various MTI FIR digital filters. This study delves into a range of VLSI Digital Signal Processing (DSP) techniques, including pipelining, parallel processing, broadcast structures, and retiming, all aimed at enhancing filter performance. These FIR structures are implemented using the Xilinx synthesis tool and deployed on the ZYNQ7 ZC702 FPGA board and the rest of the radar algorithm works on CPU in SoC configuration. Our experimental findings highlight the efficacy of retiming structures in optimizing pipeline delays, leading to reduced latency in the filtering process. This acceleration of MTI in SoC works in realtime, demonstrates substantial advantages for Advanced Driver Assistance Systems (ADAS) applications. It is characterized by a compact footprint, low power consumption, and high processing speed, making it a strong candidate for deployment in ADAS solutions. Â© 2023 IEEE.