scholarly journals Dual-Channel Particle Filter Based Track-Before-Detect for Monopulse Radar

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Fei Cai ◽  
Hongqi Fan ◽  
Qiang Fu
Keyword(s):  
Particle Filter ◽  
Doppler Radar ◽  
Pulse Repetition Frequency ◽  
Measurement Model ◽  
Performance Comparison ◽  
Detection Performance ◽  
Actual Measurement ◽  
Low Snr ◽  
Dual Channel ◽  
Track Before Detect

A particle filter based track-before-detect (PF-TBD) algorithm is proposed for the monopulse high pulse repetition frequency (PRF) pulse Doppler radar. The actual measurement model is adopted, in which the range is highly ambiguous and the sum and difference channels exist in parallel. A quantization method is used to approximate the point spread function to reduce the computation load. The detection decisions of the PF-TBD are fed to a binary integrator to further improve the detection performance. Simulation results show that the proposed algorithm can detect and track the low SNR target efficiently. The detection performance is improved significantly for both the single frame and the multiframe detection compared with the classical detector. A performance comparison with the PF-TBD using sum channel only is also supplied.

Multiple Model Particle Filter Based Track-before-Detect for Maneuvering Weak Target

2011 ◽  
Vol 30 (4) ◽  
pp. 941-944 ◽  
Author(s):  
Ya-xin Gong ◽  
Hong-wen Yang ◽  
Wei-dong Hu ◽  
Wen-xian Yu
Keyword(s):  
Particle Filter ◽  
Multiple Model ◽  
Model Particle ◽  
Track Before Detect ◽  
Weak Target

Self-Localization in Highly Dynamic Environments Based on Dual-Channel Unscented Particle Filter

Robotica ◽  
2020 ◽  
pp. 1-14
Author(s):  
Chen Hao ◽  
Liu Chengju ◽  
Chen Qijun
Keyword(s):  
Particle Filter ◽  
Humanoid Robots ◽  
Dynamic Environments ◽  
Measurement Unit ◽  
Dual Channel ◽  
Nao Robot ◽  
Unscented Particle Filter ◽  
Monte Carlo Localization ◽  
Switch Mechanism ◽  
Updating Procedure

SUMMARY Self-localization in highly dynamic environments is still a challenging problem for humanoid robots with limited computation resource. In this paper, we propose a dual-channel unscented particle filter (DC-UPF)-based localization method to address it. A key novelty of this approach is that it employs a dual-channel switch mechanism in measurement updating procedure of particle filter, solving for sparse vision feature in motion, and it leverages data from a camera, a walking odometer, and an inertial measurement unit. Extensive experiments with an NAO robot demonstrate that DC-UPF outperforms UPF and Monte–Carlo localization with regard to accuracy.

scholarly journals Using UHF-RFID Signals for Robot Localization Inside Pipelines

2021 ◽  
Author(s):  
Amal Gunatilake ◽  
Karthick Thiyagarajan ◽  
sarath kodagoda ◽  
Lasitha Piyathilaka ◽  
Poojaben Darji
Keyword(s):  
Particle Filter ◽  
Cost Effective ◽  
Measurement Model ◽  
Underground Water ◽  
Water Utilities ◽  
Robot Localization ◽  
Uhf Rfid ◽  
Localization Accuracy ◽  
Feature Based ◽  
Particle Filter Algorithm

<div>Underground water pipes are important to any country’s infrastructure. Overtime, the metallic pipes are prone to corrosion, which can lead to water leakage and pipe bursts. In order to prolong the service life of those assets, water utilities in Australia apply protective pipe linings. Long-term monitoring and timely intervention are crucial for maintaining those lining assets. However, the water utilities do not possess the comprehensive technology to achieve it. The main reasons for lacking such technology are the unavailability of sensors and accurate robot localization technologies. Feature based localization methods such as SLAM has limited use as the application of liners alters the features and the environment. Encoder based localization is not accurate enough to observe the evolution of defects over a long period of time requiring unique defect correspondence. This motivates us to explore accurate contact-less and wireless based localization methods. We propose a cost-effective localization method using UHFRFID signals for robot localization inside pipelines based on Gaussian process combined particle filter. Experiments carried out in field extracted pipe samples from the Sydney water pipe network show that using the RSSI and Phase data together in the measurement model with particle filter algorithm improves the localization accuracy up to 15 centimeters precision.</div>

Mine detection performance comparison between manual sweeping and tele-operated robotic system

2010 ◽  
Author(s):  
Herman Herman ◽  
Todd Higgins ◽  
Olga Falmier ◽  
Jean-Sebastien Valois ◽  
Jeff McMahill
Keyword(s):  
Performance Comparison ◽  
Robotic System ◽  
Detection Performance ◽  
Mine Detection

A Diffraction Measurement Model and Particle Filter Tracking Method for RSS-Based DFL

2015 ◽  
Vol 33 (11) ◽  
pp. 2391-2403 ◽  
Author(s):  
Zhenghuan Wang ◽  
Heng Liu ◽  
Shengxin Xu ◽  
Xiangyuan Bu ◽  
Jianping An
Keyword(s):  
Particle Filter ◽  
Measurement Model ◽  
Diffraction Measurement ◽  
Tracking Method

scholarly journals Speed Calibration and Traceability for Train-Borne 24 GHz Continuous-Wave Doppler Radar Sensor

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1230
Author(s):  
Lei Du ◽  
Qiao Sun ◽  
Jie Bai ◽  
Xiaolei Wang ◽  
Tianqi Xu
Keyword(s):  
Continuous Wave ◽  
Doppler Radar ◽  
Single Channel ◽  
Full Range ◽  
Calibration Method ◽  
Simulation System ◽  
Radar Sensor ◽  
Dual Channel ◽  
Calibration Methods ◽  
24 Ghz

The 24 GHz continuous-wave (CW) Doppler radar sensor (DRS) is widely used for measuring the instantaneous speed of moving objects by using a non-contact approach, and has begun to be used in train-borne movable speed measurements in recent years in China because of its advanced performance. The architecture and working principle of train-borne DRSs with different structures including single-channel DRSs used for freight train speed measurements in railway freight dedicated lines and dual-channel DRSs used for speed measurements of high-speed and urban rail trains in railway passenger dedicated lines, are first introduced. Then, the disadvantages of two traditional speed calibration methods for train-borne DRS are described, and a new speed calibration method based on the Doppler shift signal simulation by imposing a signal modulation on the incident CW microwave signal is proposed. A 24 GHz CW radar target simulation system for a train-borne DRS was specifically realized to verify the proposed speed calibration method for a train-borne DRS, and traceability and performance evaluation on simulated speed were taken into account. The simulated speed range of the simulation system was up to (5~500) km/h when the simulated incident angle range was within the range of (45 ± 8)°, and the maximum permissible error (MPE) of the simulated speed was ±0.05 km/h. Finally, the calibration and uncertainty evaluation results of two typical train-borne dual-channel DRS samples validated the effectiveness and feasibility of the proposed speed calibration approach for a train-borne DRS with full range in the laboratory as well as in the field.

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