Time Delay Estimation in Radar System using Fuzzy Based Iterative Unscented Kalman Filter T. Jagadesh 1,2 and B. Sheela Rani 3,* 1 Faculty of Electronics Engineering, Sathyabama Institute of Science and Technology, Chennai, 600119, India 2 Department of ECE, KPR Institute of Engineering and Technology, Coimbatore, 641407, India 3 Sathyabama Institute of Science and Technology, Chennai, 600119, India *Corresponding Author: B. Sheela Rani. Email: kavisheela66@gmail.com Received: 13 January 2022; Accepted: 06 April 2022 Abstract: RSs (Radar Systems) identify and trace targets and are commonly employed in applications like air traffic control and remote sensing. They are necessary for monitoring precise target trajectories. Estimations of RSs are non- linear as the parameters TDEs (time delay Estimations) and Doppler shifts are computed on receipt of echoes where EKFs (Extended Kalman Filters) and UKFs (Unscented Kalman Filters) have not been examined for computations. RSs, cer- tain times result in poor accuracies and SNRs (low signal to noise ratios) espe- cially, while encountering complicated environments. This work proposes IUKFs (Iterated UKFs) to track online filter performances while using optimiza- tion techniques to enhance outcomes. The use of cost functions can assist state corrections while lowering costs. A new parameter is optimized using MCEHOs (Mutation Chaotic Elephant Herding Optimizations) by linearly approximating system non-linearity where OIUKFs (Optimized Iterative UKFs) predict a target's unknown parameters. To obtain optimal solutions theoretically, OIUKFs take less iteration, resulting in shorter execution times. The proposed OIUKFs provide numerical approximations which are derivative-free implementations. Simulation evaluation results with estimators show better performances in terms of reduced NMSEs (Normalized Mean Square Errors), RMSEs (Root Mean Squared Errors), SNRs, variances, and better accuracies than current approaches. Keywords: Radar system; unscented kalman filter; extended kalman filter; optimized iterative unscented kalman filter; mutation chaotic elephant herding optimization; time delay estimation 1 Introduction Target identifications/tracking, management of air traffic, and remote sensing are all common use of RSs [1,2] where transmitters send signal bursts, and receivers receive dispersed versions of those signals. The scattering of signals is measured using TDEs and Doppler shifts in received signals and the target’s range and radial velocities are computed. These measurements are employed as measurements in RSs [3]. The fundamental concept of Radars is similar to that of sound wave reflection. Radars detect and locate This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Computer Systems Science & Engineering DOI: 10.32604/csse.2023.027239 Article ech T Press Science