Our paper considers the distinctive route frameworks and tries to recognize the best reasonable route system for Bangladesh. It is required as additional satellites will enhance execution for all applications, and particularly where satellite signs can be clouded, for example, in urban gullies, under tree shelters, or in open-cut mines. The advantages of the normal additional satellites and their signs are expanded accessibility, exactness, congruity, and dependability.

Due to passive tracking, fire and forget capabilities and ease of operation of guided missiles have emerged as an important anti-aircraft arsenal. Detection of target in real time is a difficult task when object is dynamic and even harder when the object tends to move at speed counted in Mach numbers. Moving target detection is a key area in image processing, infusion of this technology to the purpose of tracking target and destroying as in guided missiles can be very effective as it will reduce network links, and GPS navigation in aggressive electronic warfare environments. Detecting moving objects in real-time is a challenging problem due to the computational limits and the motions of the camera. In this paper, we suggest a method for dynamic object detection and tracking on non-stationary cameras running within few milliseconds (ms) on a PC, and real-time on mobile devices. Detecting of object by background subtraction method does not give better results when object is moving very fast, object is very tiny and presence of lighting effect. In order to overcome these troubles, we propose a new method for Moving object Detection in Dynamic Background along with the development of a guided missile using the process. It achieves dynamic landscape using certain possibility of time and subsequent frame difference method and addresses the difficult scenario, where object is moving very fast and background changes frequently. The experimental results show that the proposed method can detect moving object more efficiently and completely in both cases online as well as offline video. The results indicate that the proposed algorithm outperforms the majority of earlier state-of-the-art algorithms not only in terms of accuracy, but also in terms of processing speed.