Abstract
This paper proposes a joint path planning and transmit resource scheduling (JPP-TRS) algorithm for target tracking in airborne radar networks. The aim of our algorithm is to achieve the better target tracking accuracy by cooperatively adjusting the path planning, transmit power, dwell time, waveform bandwidth, and pulse length of each airborne radar, while satisfying the predefined low probability of intercept (LPI) performance requirement and given system resource budgets. The Bayesian Cramér-Rao lower bound (BCRLB) and probability of intercept of the underlying system are derived and utilized to gauge the target tracking accuracy and LPI performance, respectively. Since the JPP-TRS problem is a non-convex and non-linear optimization model, we put forward a fast and efficient three-step solution method to tackle the above problem. Numerical results are provided to verify the superior performance of our proposed algorithm compared with other existing schemes.
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References
Lu, X.J., Kong, L.J., Sun, J., Yuan, Y.: Joint online route planning and power allocation for multitarget tracking in airborne radar systems. In: 2020 IEEE Radar Conference, pp. 1-6 (2020)
Zhou, K., Roumeliotis, S.I.: Optimal motion strategies for range-only constrained multisensor target tracking. IEEE Trans. Robot. 24, 1168–1185 (2008)
Tharmarasa, R., Kirubarajan, T., Lang, T.: Joint path planning and sensor subset selection for multistatic sensor networks. In: Proceedings of the 2009 IEEE Symposium on Computational Intelligence in Security and Defense Applications, pp. 1-8 (2009)
Chen, P., Zheng, L., Wang, X.D., Li, H.B., Wu, L.N.: Moving target detection using colocated MIMO radar on multiple distributed moving platforms. IEEE Trans. Signal Process. 65, 4670–4683 (2017)
Nutalapati, M.K., Bedi, A.S., Rajawat, K., Coupechoux, M.: Online trajectory optimization using inexact gradient feedback for time-varying environments. IEEE Trans. Signal Process. 68, 4824–4838 (2020)
Yan, J.K., Liu, H.W., Pu, W.Q., Zhou, S.H., Bao, Z.: Joint beam selection and power allocation for multiple target tracking in netted colocated MIMO radar system. IEEE Trans. Signal Process. 64, 6417–6427 (2016)
Li, X., Cheng, T., Su, Y., Peng, H.: Joint time-space resource allocation and waveform selection for the collocated MIMO radar in multiple targets tracking. Signal Process. 176, 1–10 (2020)
Yan, J.K., Dai, J.H., Pu, W.Q., Liu, H.W., Greco, M.: Target capacity based resource optimization for multiple target tracking in radar network. IEEE Trans. Signal Process. 69, 2410–2421 (2021)
Zhang, H.W., Liu, W.J., Zhang, Z.J., Lu, W.L., Xie, J.W.: Joint target assignment and power allocation in multiple distributed MIMO radar networks. IEEE Syst. J. 15, 694–704 (2021)
Nguyen, N.H., Dogancay, K., Davis, L.M.: Joint transmitter waveform and receiver path optimization for target tracking by multistatic radar system. In: 2014 IEEE Workshop on Statistical Signal Processing, pp. 444-447 (2014)
Wang, Y.J., Shi, C.G., Wang, F., Zhou, J.J.: Collaborative transmit resource scheduling and waveform selection for target tracking in multistatic radar system. IET Radar Sonar Navigation. 15, 209–225 (2021)
Shrestha, A.P., Yoo, S.: Optimal resource allocation using support vector machine for wireless power transfer in cognitive radio networks. IEEE Trans. Vehic. Technol. 67, 8525–8535 (2018)
Acknowledgement
This work was supported in part by the National Natural Science Foundation of China under Grant 61801212, in part by the Key Laboratory of Equipment Pre-Research Foundation under Grant 6142401200402, in part by the Natural Science Foundation of Jiangsu Province under Grant BK20180423, in part by the National Aerospace Science Foundation of China under Grant 20200020052002 and Grant 20200020052005, in part by National Defense Science and Technology Innovation Special Zones, and in part by Key Laboratory of Radar Imaging and Microwave Photonics (Nanjing Univ. Aeronaut. Astronaut.), Ministry of Education, Nanjing, China.
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Shi, C., Wang, Y., Dai, X., Wang, F., Zhou, J. (2022). Joint Path Planning and Transmit Resource Scheduling Algorithm for Target Tracking in Airborne Radar Networks. In: Wu, M., Niu, Y., Gu, M., Cheng, J. (eds) Proceedings of 2021 International Conference on Autonomous Unmanned Systems (ICAUS 2021). ICAUS 2021. Lecture Notes in Electrical Engineering, vol 861. Springer, Singapore. https://doi.org/10.1007/978-981-16-9492-9_32
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DOI: https://doi.org/10.1007/978-981-16-9492-9_32
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