Target detection in multistatic radar networks

Date

2025-8-29

Author

Arslan, Anıl

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Advances in military technology have made possible targets with reduced back scattering coefficient, which is increasingly challenging for conventional radar systems. Although previously developed and deployed, multistatic radar networks can overcome these challenges and have gained renewed interest thanks to advances in hardware and signal processing. These networks offer superior detection performance for low-radar-cross-section targets compared to conventional monostatic radar systems, thanks to their spatially distributed nodes. Spatial diversity requires a wide separation between nodes relative to the target, ensuring that returns are independent across receivers and different sources of information about the target are available. This independence makes coherent integration for target detection impractical and eliminates the need for phase synchronization across the network, which may be challenging, especially for widely separated multistatic radar networks. As a result, techniques such as noncoherent integration and binary integration have practical importance for widely separated multistatic radar networks. On the other hand, nodes need to communicate with a fusion center for joint target detection and parameter estimation, thereby increasing the importance of optimizing communication demand. Binary integration, where only the binary result of target presence at each receiver is sent to the fusion center, is the most communication-efficient approach, but with very coarse of information. In contrast, noncoherent integration utilizes more information and requires more communication load. This thesis examines performance metrics both theoretically and through simulation, for widely separated multistatic networks under different integration techniques and different node configurations.

Subject Keywords

Multistatic radar, Distributed target detection, Selective square law integration, Spatial diversity, Phase Synchronization

URI

https://hdl.handle.net/11511/116035

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Graduate School of Natural and Applied Sciences, Thesis