This research paper presents an innovative approach to object detection in drones utilizing the HB100 radar module. The primary objective of this study was to develop a system capable of capturing both stationary and moving objects, regardless of the visibility conditions in the surrounding environment. By integrating the HB100 radar module into the drone’s architecture, real-time object detection and tracking capabilities were achieved, significantly enhancing the drone’s perception abilities. The experimental setup involved integrating the HB100 radar module for a quad-copter drone external platform linked to the base station; enabling the collection of radar signals and subsequent processing for object detection. Various stationary and moving objects were employed to evaluate the effectiveness of the system under different environmental conditions, including scenarios with limited visibility, such as fog or darkness and power-bandwidth. The HB100 radar module operates based on the principle of Doppler radar. It emits continuous wave (CW) signals and detects the Doppler shift in the reflected signals to 1(zero crossing). This article motivates on the RGB Charged Coupled Device or night vision camera and Synthetic Aperture Radar (SAR) integration at UAV or drone platform. The on board Arduino micro-controller trigger the external circuit of the airborne transceiver. The modular change of the COFFE CAN radar digital signal processing (DSP) and HB100 radar infer the omni-direction antenna piece out with the directional DSP. As a result, the wide sense stationary (WSS) signal forms image of inner-wall and outer wall but clinging on syphoned based diffractive medium caused on deliverable environmental conditions. The changing to standing wave in a reflecting wall distance or determine the presence and movement of objects. The safety and mine hazard conditions the flooding and double differentiating checks it accelerating values on positive and negative sides forming colored pattern of moving directional object movement. The phase patterns of these images are the region of convergence using Z transform on those images changing values to spirals. Lastly, the issues of whole setup is tested with load balancing on both on weight and electric circuits DC due to not operating shunting based on electron discharge phenomenon in any environmental conditions.