Browsing by Author "Raju, M.K."

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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. © 2023 IEEE.
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    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. © 2023 IEEE.
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    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 × 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. © 2023 IEEE.