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Author: search.filters.author.Tantiparimongkol, Lalida

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    Joint Iterative Satellite Pose Estimation and Particle Swarm Optimization
    (2025-02-01)
    Kamsing, Patcharin
    ;
    Cao, Chunxiang
    ;
    Zhao, You
    ;
    Boonpook, Wuttichai
    ;
    Tantiparimongkol, Lalida
    Satellite pose estimation (PE) is crucial for space missions and orbital maneuvering. High-accuracy satellite PE could reduce risks, enhance safety, and help achieve the objectives of close proximity and docking operations for autonomous systems by reducing the need for manual control in the future. This article presents a joint iterative satellite PE and particle swarm optimization (PE-PSO) method. The PE-PSO method uses the number of batches derived from satellite PE as the number of particles and keeps the number of epochs from the satellite PE process as the number of epochs for PSO. The objective function of PSO is the training function of the implemented network. The output obtained from the previous objective function is applied to update the new positions of the particles, which serve as the inputs of the current training function. The PE-PSO method is tested on synthetic Soyuz satellite image datasets acquired from the Unreal Rendered Spacecrafts On-Orbit Datasets (URSOs) under different preset hyperparameters. The proposed method significantly reduces the incurred loss, especially during the batch-processing operation of each epoch. The results illustrate the accuracy improvement attained by the PE-PSO method over epoch processing, but its time consumption is not distinct from that of the conventional method. In addition, PE-PSO achieves better performance by reducing the mean position estimation error by 13.1% and the mean orientation estimation error on the testing dataset by 29.1% based on the pretrained weights of Common Objects in Context (COCO). Additionally, PE-PSO improves the accuracy of the Soyuz_hard-based weight by 7.8% and 0.3% in terms of the mean position estimation error and mean orientation estimation error, respectively.
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    IR-UWB pulse generation using FPGA scheme for through obstacle human detection
    (2020-07-01)
    Tantiparimongkol, Lalida
    ;
    Phasukkit, Pattarapong
    This research proposes a scheme of field programmable gate array (FPGA) to generate an impulse-radio ultra-wideband (IR-UWB) pulse. The FPGA scheme consists of three parts: digital clock manager, four-delay-paths stratagem, and edge combiner. The IR-UWB radar system is designed to detect human subjects from their respiration underneath the rubble in the aftermath of an earthquake and to locate the human subjects based on range estimation. The proposed IR-UWB radar system is experimented with human subjects lying underneath layers of stacked clay bricks in supine and prone position. The results reveal that the IR-UWB radar system achieves a pulse duration of 540 ps with a bandwidth of 2.073 GHz (fractional bandwidth of 1.797). In addition, the IR-UWB technology can detect human subjects underneath the rubble from respiration and identify the location of human subjects by range estimation. The novelty of this research lies in the use of the FPGA scheme to achieve an IR-UWB pulse with a 2.073 GHz (117 MHz–2.19 GHz) bandwidth, thereby rendering the technology suitable for a wide range of applications, in addition to through-obstacle detection.
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    Designing of uwb pulse generation in fpga based on delay line method for human range through the wall detecting application
    (2019-07-01)
    Tantiparimongkol, Lalida
    ;
    Phasukkit, Pattarapong
    This paper intends to present UWB generation by FPGA for further using in human detecting through the wall. In this experiment, we use method of digital circuit synthesize by Verilog coding into FPGA. Which coding method is the implementation of Delay line based theory. This experiment could produce pulse with pulse width 575ps and bandwidth of 3.83GHz. The purpose is applied for radar through the wall for human range detection application. There're experiment with human detection system which locate human movement from Doppler frequency and standard deviation. The experiment is shown at range of detection at 1m, 1.5m and 2m which the result shows output pulse from FPGA could detect human at these ranges.