Chenguang Shi
Optimal Power Allocation Strategy in a Joint Bistatic Radar and Communication System Based on Low Probability of Intercept
Shi, Chenguang; Wang, Fei; Salous, Sana; Zhou, Jianjiang
Abstract
In this paper, we investigate a low probability of intercept (LPI)-based optimal power allocation strategy for a joint bistatic radar and communication system, which is composed of a dedicated transmitter, a radar receiver, and a communication receiver. The joint system is capable of fulfilling the requirements of both radar and communications simultaneously. First, assuming that the signal-to-noise ratio (SNR) corresponding to the target surveillance path is much weaker than that corresponding to the line of sight path at radar receiver, the analytically closed-form expression for the probability of false alarm is calculated, whereas the closed-form expression for the probability of detection is not analytically tractable and is approximated due to the fact that the received signals are not zero-mean Gaussian under target presence hypothesis. Then, an LPI-based optimal power allocation strategy is presented to minimize the total transmission power for information signal and radar waveform, which is constrained by a specified information rate for the communication receiver and the desired probabilities of detection and false alarm for the radar receiver. The well-known bisection search method is employed to solve the resulting constrained optimization problem. Finally, numerical simulations are provided to reveal the effects of several system parameters on the power allocation results. It is also demonstrated that the LPI performance of the joint bistatic radar and communication system can be markedly improved by utilizing the proposed scheme.
Citation
Shi, C., Wang, F., Salous, S., & Zhou, J. (2017). Optimal Power Allocation Strategy in a Joint Bistatic Radar and Communication System Based on Low Probability of Intercept. Sensors, 17(12), Article 2731. https://doi.org/10.3390/s17122731
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 22, 2017 |
Online Publication Date | Nov 25, 2017 |
Publication Date | Nov 25, 2017 |
Deposit Date | Dec 14, 2017 |
Publicly Available Date | Dec 14, 2017 |
Journal | Sensors |
Publisher | MDPI |
Peer Reviewed | Peer Reviewed |
Volume | 17 |
Issue | 12 |
Article Number | 2731 |
DOI | https://doi.org/10.3390/s17122731 |
Public URL | https://durham-repository.worktribe.com/output/1342349 |
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Copyright Statement
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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