Browsing by Author "Kumar, S.A."

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    Bistatic Inverse Synthetic Aperture Radar Imaging of Automotive Targets at Millimeter Frequencies
    (Institute of Electrical and Electronics Engineers Inc., 2023) Kumar, S.A.; Ram, S.S.; Srihari, P.
    High-resolution inverse synthetic aperture radar (ISAR) images of road vehicles at millimeter wave frequencies provide useful information regarding the size, shape, number of wheels, and nature of the target trajectory. They are thus effective features for target classification. However, in some geometrically adverse scenarios, it may not be possible to generate ISAR images in monostatic radar conditions. Here, bistatic ISAR images generated from well separated transmitting and receiving antennas may overcome the limitations of the monostatic geometry or supplement the information obtained from monostatic radar. In this paper, we present the bistatic ISAR radar images of a car from multiple orientations and aspects. The radar data are gathered from simulations using computer-animated design models of the car along a turning trajectory. Electromagnetic modeling of the radar scattering combines a point scatterer model of the extended automotive target along with shadowing based on ray tracing. © 2023 IEEE.
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    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. © 2024 IEEE.