Date

2023-1

Author

Yazıcı, Ayhan

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Low radar cross section and capability to fly at low speeds make drones challenging targets for radar detection. In the presence of ground moving targets, the frequency spectrum is also crowded which makes the detection of the drones more difficult. Micro-Doppler effect is the main feature used to discriminate drone from other targets and clutter. Typically, discrimination is performed after the detection of all the targets. Especially in target dense environments, such as cities, typical approach requires high processing power in order detect and classify all of the targets. Coverage is also another problem of the typical monostatic radar based drone detection in cities. Coverage of monostatic radar is easily blocked by buildings. In order to cope with these problems distributed multi-input multi-output (MIMO) continuous wave (CW) radar using MIMO cyclic spectral density (CSD) analysis (MCSD) method is proposed in this thesis. MCSD method separates drones and other targets and clutter in cyclic frequency domain. In order to make system simple and low cost, a network of continuous wave radars is used and the localization is performed based on Doppler only localization approach. The simulations and experimental results show the proof of the concept. Performance and cost analysis of MCSD method is also analyzed in the thesis.

Subject Keywords

Cyclostationary, Deinterleaving, Doppler-only localization, Drone detection, MIMO radar, Radar

URI

https://hdl.handle.net/11511/102009

Collections

Graduate School of Natural and Applied Sciences, Thesis