Development of a New Fuzzy Logic Based Algorithm for Tracking Targets

Radio-electronic means, including equipment for transmissions, radio-location, broadcasting, and navigation,
allow the execution of various research missions and combat forces management. Determining the target
coordinates and directing the armament towards them, obtaining and processing data about enemies, ensuring
the navigation of ships, planes and outer atmospheric means, transmitting orders, decisions, reports and other
necessary information for the armed forces; these are only some of the possibilities of radio-electronic
technology. Fuzzy logic allows the linguistic description of the laws of command, operation and control of a
system. When working with complex and nonlinear systems, it can often be observed that, as their complexity
increases, there is a decrease in the significance of the details in describing the global behavior of the system.
Even though such an approach may seem inadequate, it is often superior and less laborious than a rigorous
mathematical approach. The main argument in favor of fuzzy set theory is to excel in operating with imprecise,
vague notions. This article demonstrates the superiority of a fuzzy tracking system over the standard Kalman
filter tracking system under the conditions of uneven accelerations and sudden change of direction of the targets,
as well as in the case of failure to observe the target during successive scans. A cascading Kalman filtering
algorithm was used to solve the speed ambiguity and to reduce the measurement error in real-time radar
processing. The cascade filters are extended Kalman filters with controlled gain using fuzzy logic for tracking
targets using radar equipment under difficult tracking conditions. The main directions for further research are as
follows: the implementation of fuzzy logic in a real target tracking application under difficult conditions. As an
initial approach, a classical alpha-beta system can be modified in order to determine alpha and beta coefficients
by fuzzy logic. Based on the fuzzy gain filter presented in this article, an automated structure can be developed,
which provides the tracking system with real-time updated values for alpha and beta coefficients.