Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Author: search.filters.author.Pardhasaradhi, B.Subject: search.filters.subject.automotive radar

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    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 97.74± 0.34 accuracy (with 18.32 MB size) compared to the denseNet201 of 99.13± 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. © 2024 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.