A direction tracking algorithm based on the repulsive force model with low SNR in MIMO HF sky-wave radar

Millimeter-wave radar has been widely used in intelligent vehicle target detection. However, there are three difficulties in radar-based target tracking in curves. First, there are massive data association calculations with poor accuracy. Second, the lane position relationship of target-vehicle cannot be identified accurately. Third, the target tracking algorithm has poor robustness and accuracy. A target tracking algorithm framework on curved road is proposed herein. The following four algorithms are applied to reduce data association calculations and improve accuracy. (1) The data rationality judgment method is employed to eliminate target measurement data outside the radar detection range. (2) Effective target life cycle rules are used to eliminate false targets and clutter. (3) Manhattan distance clustering algorithm is used to cluster multiple data into one. (4) The correspondence between the measurement data received by the radar and the target source is identified by the nearest neighbor (NN) data association. The following three algorithms aim to derive the position relationship between the ego-vehicle and the target-vehicles. (1) The lateral speed is obtained by estimating the state of motion of the ego-vehicle. (2) An algorithm for state compensation of target motion is presented by considering the yaw motion of the ego-vehicle. (3) A target lane relationship recognition model is built. The improved adaptive extended Kalman filter (IAEKF) is used to improve the target tracking robustness and accuracy. Finally, the vehicle test verifies that the algorithms proposed herein can accurately identify the lane position relationship. Experiments show that the framework has higher target tracking accuracy and lower computational time.

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Bi-Station Multi-Target Tracking Using Range and Doppler Measurements

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.329.338 ◽

2013 ◽

Vol 329 ◽

pp. 338-343

Author(s):

Tian Jiao Fu ◽

Li Guo Zhang ◽

Jian Yue Ren

Keyword(s):

Target Tracking ◽

High Frequency ◽

Radar System ◽

Tracking Algorithm ◽

Range Finding ◽

Wave Radar ◽

Multi Target Tracking ◽

Actual Environment ◽

Simulation Results ◽

Ground Wave

The azimuthal measurements of the high frequency ground wave radar are poor in an actual environment, which can cause the plots highly decentralized and damage the formation of the over-the-horizon tracks. To solve the problem, a new radar system is proposed to triangulate target tracks using range and Doppler measurements only. On the basis of the analysis of the characteristics of the range-finding location, a multi-target tracking algorithm under non-clutter condition is given in this paper, which further improves the tracking algorithm of this system. Simulation results show the effectiveness of this method.

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An Efficient Ship Automatic Collision Avoidance Method Based on Modified Artificial Potential Field

Journal of Marine Science and Engineering ◽

10.3390/jmse10010003 ◽

2021 ◽

Vol 10 (1) ◽

pp. 3

Author(s):

Zhongxian Zhu ◽

Hongguang Lyu ◽

Jundong Zhang ◽

Yong Yin

Keyword(s):

Collision Avoidance ◽

Potential Field ◽

Repulsive Force ◽

Adjustable Parameter ◽

Artificial Potential Field ◽

Force Model ◽

Safe Distance ◽

International Regulations ◽

Motion Characteristics ◽

Approach Time

A novel collision avoidance (CA) algorithm was proposed based on the modified artificial potential field (APF) method, to construct a practical ship automatic CA system. Considering the constraints of both the International Regulations for Preventing Collisions at Sea (COLREGS) and the motion characteristics of the ship, the multi-ship CA algorithm was realized by modifying the repulsive force model in the APF method. Furthermore, the distance from the closest point of approach-time to the closest point of approach (DCPA-TCPA) criterion was selected as the unique adjustable parameter from the perspective of navigation practice. Collaborative CA experiments were designed and conducted to validate the proposed algorithm. The results of the experiments revealed that the actual DCPA and TCPA agree well with the parameter setup that keeps the ship at a safe distance from other ships in complex encountering situations. Consequently, the algorithm proposed in this study can achieve efficient automatic CA with minimal parameter settings. Moreover, the navigators can easily accept and comprehend the adjustable parameters, enabling the algorithm to satisfy the demand of the engineering applications.

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An implementation of tracking algorithm for over-the-horizon surface wave radar

2016 24th Telecommunications Forum (TELFOR) ◽

10.1109/telfor.2016.7818820 ◽

2016 ◽

Cited By ~ 4

Author(s):

Nikola Stojkovic ◽

Dejan Nikolic ◽

Bojan Dzolic ◽

Nikola Tosic ◽

Vladimir Orlic ◽

...

Keyword(s):

Surface Wave ◽

Tracking Algorithm ◽

Wave Radar

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An OPMA for Robust Mutual Coupling Coefficients Estimation of URA with Single Snapshot in MIMO HF Sky-Wave Radar

International Journal of Antennas and Propagation ◽

10.1155/2016/7515028 ◽

2016 ◽

Vol 2016 ◽

pp. 1-11

Author(s):

Yuguan Hou ◽

Qingguo Jin ◽

Shaochuan Wu ◽

Zhuoming Li

Keyword(s):

Mutual Coupling ◽

Signal To Noise Ratio ◽

Mean Shift ◽

Success Probability ◽

Doa Estimation ◽

Coupling Coefficients ◽

Music Algorithm ◽

Low Snr ◽

Wave Radar ◽

Single Snapshot

Due to the fluctuation of the signal-to-noise ratio (SNR) and the single snapshot case in the MIMO HF sky-wave radar system, the accuracy of the online estimation of the mutual coupling coefficients matrix of the uniform rectangle array (URA) might be degraded by the classical approach, especially in the case of low SNR. In this paper, an Online Particle Mean-Shift Approach (OPMA) is proposed, which is to get a relatively more effective estimation of the mutual coupling coefficients matrix with the low SNR. Firstly, the spatial smoothing technique combined with the MUSIC algorithm of URA is introduced for the DOA estimation of the multiple targets in the case of single snapshot which are taken as coherent sources. Then, based on the idea of the particle filter, the online particles with a moderate computational complexity are used to generate some different estimation results. Finally, the mean-shift algorithm is applied to get a more robust estimate of the equivalent mutual coupling coefficients matrix. The simulation results demonstrate the validity of the proposed approach in terms of the success probability, the statistics of bias, and the variance. The proposed approach is more robust and more accurate than the other two approaches.

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