Digital video broadcasting satellite-based passive forward scatter radar for drone detection based on micro Doppler analysis

The exponential growth of drone usage and the posing threats by the users such as unauthorized imaging and filming in restricted areas, illegal surveillance, air collision, drugs smuggle, terrorist attacks, RF jamming among others, became alarming. Several efforts were made to detect the drone to curtail the menace. Attempt such as acoustic, camera, cascaded audio-visual, radio frequency (RF) and other non-technical approaches were among the efforts made in detecting a drone. Radar system is another method used for surveillance, detection and tracking of ground moving and airborne targets. This thesis presented a micro-Doppler analysis for drone detection and identification by using digital video broadcasting satellite (DVB-S) based passive forward scatter radar (PFSR) systems. The passive radar ability to exploit the available illuminators for targets’ detection and its key benefits were the motivating factor of its implementation. Besides, FSR as a special mode of bistatic radar with an enhanced performance and attracting features, making it a good candidate for this work. Thus, this thesis, described how a DVB-S based PFSR system, for drone detection based on its micro-Doppler was implemented. A theoretical model was designed, simulated, and validated experimentally, for both the Doppler due to drone linear motion and the micro-Doppler signature in FSR geometry. The results were promising especially for the “Facing-Rx” scenario and can serve as a model for Doppler analysis of the drone in FSR geometry. In a feasibility study, the DVB-S signal ambiguities guarantees a good range resolution of 4.17m that can differentiate a velocity of 0.027m/s. Irrespective of the blade material and orientation, an appreciable RCS was achieved in FS mode with highest RCS whenever the blade is facing e-field direction e.g. 0.736 dBm for Perfect Electrical Conductor (PEC) material. A SNR of 4 dB above the bistatic threshold of 13 dB was achieved hence, with the FSR receiving system, a reasonable processing gains (<normal i.e. 55-75 dB) is enough to achieve the sensitivity level of the receiver. The direct power (Pdir) arriving the antenna front-end is -112.1324 dBw, which is within the practical value. A Measat3a/3/3b signal was acquired and used for actual detection of the drone over a 40 m target-receiver distance. An empirical mode decomposition (EMD) algorithm was then used to extract the feature vectors present in the acquired signature. This involve the Doppler and the micro-Doppler component due to the rotating blades. The results were promising and conformed with the theoretical assumptions and that of the FSR system. The extracted micro-Doppler served as a strong hold for the identification of the detected drone. It is also used to identify the direction of flight of the drone. The PFSR system is therefore considered efficient in detecting a low profiled airborne target.

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