Intensive Review of Drones Detection and Tracking: Linear Kalman Filter Versus Nonlinear Regression, an Analysis Case
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- Written by Nidal Al-Dmour
- Category: Computer Engineering
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AbstractIn this paper, an extensive review for objects and drones detection and tracking (AUV’s) is presented. The most famous and used technique for drones tracking is Kalman Filters (KFs) in its different types. The paper presents analysis and comparisons for drones tracking based on Linear Kalman Filters (LKF) comparing to tracking using Polynomial Nonlinear Regression (PNR) techniques. Interesting findings reflect the need for both methods at different circumstances depending on the noise conditions of the sensors. On the other hand, many new methods such as Artificial Intelligence (AI) based techniques are recently used in drones detection and recognition. Those methods could come separate or combined with tracking. The paper presents the state of the art methods used in detection and tracking of objects and drones with adequate analysis for the standard methods of LKF and PNR.Keywords: Objects tracking, Objects Detection, Kalman Filters, Nonlinear Regression, Ground Truth.