Joint Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking of Unmanned Cluster Based on Fuzzy Logic Reasoning
Abstract
:1. Introduction
2. System Structure
2.1. Target Motion Model
2.2. Measurement Model
2.3. Fusion Center
3. Radar Cluster
3.1. Target Priority Based on Fuzzy Logic Reasoning
3.1.1. Fuzzification
3.1.2. Fuzzy Rule
3.1.3. Fuzzy Inference
3.1.4. Defuzzification
3.2. Radar Clustering Strategy Based on the Target Priority
- Select the highest priority value from the matrix . Then the radar mk corresponding to is assigned to the radar cluster that will track the target nk. Set all values of the matrix in line mk to zeros.
- Repeat step 1 to assign radars to each target. If the number of radars assigned to a target has reached the preset require number MT, set all values in the column of the target in matrix to 0. Figure 5 shows the flow of radar clustering algorithm.
4. Management of Power Resource of Radar Networks
4.1. BCRLB of Target Tracking
4.2. Power Resource Management Opportunity Constraint Programming Model
4.3. Model Solving Method
4.3.1. Stochastic Simulation
Algorithm 1. Stochastic simulation algorithm |
Step (1): Let . |
Step (2): Generate N sets of RCS vector samples from sample space . |
Step (3): If , then . Repeat steps 2 to 3. |
Step (4): Let . |
Step (5): If , then satisfies the confidence level , otherwise it does not. |
4.3.2. Hybrid Intelligent Algorithm
Algorithm 2. Stochastic simulation algorithm |
Step (1): According to the target motion equation under zero process noise, predict the state vector at the moment;. |
Step (2): Initialize population S and stain length N, then verify the feasibility of chromosomes using random simulation. |
Step (3): Hybridize and mutate chromosomes, use random simulation to verify whether the chromosomes meet the constraints, and correct those chromosomes that do not meet the constraints. |
Step (4): Calculate the objective function value of all chromosomes, and calculate the fitness function value of each stain according to the objective function value. |
Step (5): Use roulette to select chromosomes. If the requirements of the stopping rules are not met, go to (3). If the stopping rules are met, go to step (6). |
Step (6): Returns the best chromosome as the optimal radar transmit power . |
5. Target State Estimation
Algorithm 3. UKF algorithm |
Step (1): Let k = 1, initialize each radar transmit power , target state and covariance matrix . |
Step (2): The transmitting power of each radar is , get the measured value of the target, and calculate . |
Step (3): Construct the 2L + 1 sigma point set and the weights corresponding to the point set according to the following formula. Where, is a scale factor, represents the ith column of the square root of the matrix; I represents the dimension of the state vector. |
Step (4): Map the sigma point set to the predicted point set through the state transition function , and calculate the new target state and variance by weighting. |
Step (5): Map the sigma prediction point set to the new point set through the measurement equation, and calculate the mean , variance and . |
Step (6): Calculate the gain matrix and update and covariance matrix with the gain matrix. |
Step (7): According to the intelligent hybrid algorithm proposed above, predict the radar transmission power at the kth moment, let and then jump to step (2) |
6. Simulation Results and Analysis
7. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A
- IF (range is close) AND (speed is very slow) AND (identity is low risk), then (priority is Medium)
- IF (range is close) AND (speed is very slow) AND (identity is medium risk), then (priority is High)
- IF (range is close) AND (speed is very slow) AND (identity is high risk), then (priority is High)
- IF (range is close) AND (speed is slow) AND (identity is low risk), then (priority is Medium)
- IF (range is close) AND (speed is slow) AND (identity is medium risk), then (priority is High)
- IF (range is close) AND (speed is slow) AND (identity is high risk), then (priority is High)
- IF (range is close) AND (speed is medium) AND (identity is low risk), then (priority is Medium)
- IF (range is close) AND (speed is medium) AND (identity is medium risk), then (priority is High)
- IF (range is close) AND (speed is medium) AND (identity is high risk), then (priority is High)
- IF (range is close) AND (speed is fast) AND (identity is low risk), then (priority is High)
- IF (range is close) AND (speed is fast) AND (identity is medium risk), then (priority is High)
- IF (range is close) AND (speed is fast) AND (identity is high risk), then (priority is High)
- IF (range is close) AND (speed is very fast) AND (identity is low risk), then (priority is High)
- IF (range is close) AND (speed is very fast) AND (identity is medium risk), then (priority is High)
- IF (range is close) AND (speed is very fast) AND (identity is high risk), then (priority is High)
- IF (range is medium-close) AND (speed is very slow) AND (identity is low risk), then (priority is Medium)
- IF (range is medium-close) AND (speed is very slow) AND (identity is medium risk), then (priority is Medium)
- IF (range is medium-close) AND (speed is very slow) AND (identity is high risk), then (priority is Medium)
- IF (range is medium-close) AND (speed is slow) AND (identity is low risk), then (priority is Medium)
- IF (range is medium-close) AND (speed is slow) AND (identity is medium risk), then (priority is Medium)
- IF (range is medium-close) AND (speed is slow) AND (identity is high risk), then (priority is High)
- IF (range is medium-close) AND (speed is medium) AND (identity is low risk), then (priority is Medium)
- IF (range is medium-close) AND (speed is medium) AND (identity is medium risk), then (priority is Medium)
- IF (range is medium-close) AND (speed is medium) AND (identity is high risk), then (priority is High)
- IF (range is medium-close) AND (speed is fast) AND (identity is low risk), then (priority is Medium)
- IF (range is medium-close) AND (speed is fast) AND (identity is medium risk), then (priority is High)
- IF (range is medium-close) AND (speed is fast) AND (identity is high risk), then (priority is High)
- IF (range is medium-close) AND (speed is very fast) AND (identity is low risk), then (priority is Medium)
- IF (range is medium-close) AND (speed is very fast) AND (identity is medium risk), then (priority is High)
- IF (range is medium-close) AND (speed is very fast) AND (identity is high risk), then (priority is High)
- IF (range is medium) AND (speed is very slow) AND (identity is low risk), then (priority is Low)
- IF (range is medium) AND (speed is very slow) AND (identity is medium risk), then (priority is Medium)
- IF (range is medium) AND (speed is very slow) AND (identity is high risk), then (priority is Medium)
- IF (range is medium) AND (speed is slow) AND (identity is low risk), then (priority is Low)
- IF (range is medium) AND (speed is slow) AND (identity is medium risk), then (priority is Medium)
- IF (range is medium) AND (speed is slow) AND (identity is high risk), then (priority is Medium)
- IF (range is medium) AND (speed is medium) AND (identity is low risk), then (priority is Medium)
- IF (range is medium) AND (speed is medium) AND (identity is medium risk), then (priority is Medium)
- IF (range is medium) AND (speed is medium) AND (identity is high risk), then (priority is Medium)
- IF (range is medium) AND (speed is fast) AND (identity is low risk), then (priority is Medium)
- IF (range is medium) AND (speed is fast) AND (identity is medium risk), then (priority is Medium)
- IF (range is medium) AND (speed is fast) AND (identity is high risk), then (priority is High)
- IF (range is medium) AND (speed is very fast) AND (identity is low risk), then (priority is Medium)
- IF (range is medium) AND (speed is very fast) AND (identity is medium risk), then (priority is Medium)
- IF (range is medium) AND (speed is very fast) AND (identity is high risk), then (priority is High)
- IF (range is medium-far) AND (speed is very slow) AND (identity is low risk), then (priority is Low)
- IF (range is medium-far) AND (speed is very slow) AND (identity is medium risk), then (priority is Low)
- IF (range is medium-far) AND (speed is very slow) AND (identity is high risk), then (priority is Medium)
- IF (range is medium-far) AND (speed is slow) AND (identity is low risk), then (priority is Low)
- IF (range is medium-far) AND (speed is slow) AND (identity is medium risk), then (priority is Low)
- IF (range is medium-far) AND (speed is slow) AND (identity is high risk), then (priority is Medium)
- IF (range is medium-far) AND (speed is medium) AND (identity is low risk), then (priority is Low)
- IF (range is medium-far) AND (speed is medium) AND (identity is medium risk), then (priority is Low)
- IF (range is medium-far) AND (speed is medium) AND (identity is high risk), then (priority is Medium)
- IF (range is medium-far) AND (speed is fast) AND (identity is low risk), then (priority is Low)
- IF (range is medium-far) AND (speed is fast) AND (identity is medium risk), then (priority is Medium)
- IF (range is medium-far) AND (speed is fast) AND (identity is high risk), then (priority is Medium)
- IF (range is medium-far) AND (speed is very fast) AND (identity is low risk), then (priority is Low)
- IF (range is medium-far) AND (speed is very fast) AND (identity is medium risk), then (priority is Medium)
- IF (range is medium-far) AND (speed is very fast) AND (identity is high risk), then (priority is Medium)
- IF (range is far) AND (speed is very slow) AND (identity is low risk), then (priority is Low)
- IF (range is far) AND (speed is very slow) AND (identity is medium risk), then (priority is Low)
- IF (range is far) AND (speed is very slow) AND (identity is high risk), then (priority is Medium)
- IF (range is far) AND (speed is slow) AND (identity is low risk), then (priority is Low)
- IF (range is far) AND (speed is slow) AND (identity is medium risk), then (priority is Low)
- IF (range is far) AND (speed is slow) AND (identity is high risk), then (priority is Medium)
- IF (range is far) AND (speed is medium) AND (identity is low risk), then (priority is Low)
- IF (range is far) AND (speed is medium) AND (identity is medium risk), then (priority is Low)
- IF (range is far) AND (speed is medium) AND (identity is high risk), then (priority is Medium)
- IF (range is far) AND (speed is fast) AND (identity is low risk) then (priority is Low)
- IF (range is far) AND (speed is fast) AND (identity is medium risk), then (priority is Low)
- IF (range is far) AND (speed is fast) AND (identity is high risk), then (priority is Medium)
- IF (range is far) AND (speed is very fast) AND (identity is low risk), then (priority is Low)
- IF (range is far) AND (speed is very fast) AND (identity is medium risk), then (priority is Low)
- IF (range is far) AND (speed is very fast) AND (identity is high risk), then (priority is Medium)
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Fuzzy Variable | Excursion | Fuzzy Value |
---|---|---|
range | (0,360] (km) | close, medium-close, medium, medium-far, far |
speed | (0,960] (m/s) | very slow, slow, medium, fast, very fast |
target identity | (0,1] | low risk, medium risk, high risk |
priority | (0,1] | low, medium, high |
Parameter | Wavelength | Effective Bandwidth | Effective Timewidth | Sampling Interval |
---|---|---|---|---|
Value | 0.03 m | 5 MHz | 1 ms | 0.5 s |
Radar Serial Number | Position/(m, m) |
---|---|
1 | (−82,500, 0) |
2 | (−82,500, 55,000) |
3 | (−82,500, 110,000) |
4 | (−82,500, 165,000) |
5 | (−27,500, 0) |
6 | (27,500, 0) |
7 | (−27,500, 165,000) |
8 | (27,500, 165,000) |
9 | (82,500, 165,000) |
10 | (82,500, 110,000) |
11 | (82,500, 55,000) |
12 | (82,500, 0) |
Target | Initial position/(m, m) | Velocity/(m/s) |
---|---|---|
1 | (−40,000, 135,000) | (30, −520) |
2 | (31,000, 125,000) | (−310, −660) |
3 | (45,500, 29,000) | (90, 530) |
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Zhang, Y.; Pan, M.; Han, Q. Joint Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking of Unmanned Cluster Based on Fuzzy Logic Reasoning. Sensors 2020, 20, 1371. https://doi.org/10.3390/s20051371
Zhang Y, Pan M, Han Q. Joint Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking of Unmanned Cluster Based on Fuzzy Logic Reasoning. Sensors. 2020; 20(5):1371. https://doi.org/10.3390/s20051371
Chicago/Turabian StyleZhang, Yuanshi, Minghai Pan, and Qinghua Han. 2020. "Joint Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking of Unmanned Cluster Based on Fuzzy Logic Reasoning" Sensors 20, no. 5: 1371. https://doi.org/10.3390/s20051371