Low Altitude and Small Target Tracking Based on IMM L-M Cubature Kalman Filter

At present, low waltitude, and small target (LST) tracking is an essential part of air defense. The essence of LST tracking is using a filtering algorithm to estimate the target’s trace. As most LST systems are non-linear, non-linear filtering is essential those systems. As a result, we choose Cubature Kalman Filter (CKF) as our filter due to CKF’s good performance in nonlinear systems. For LST tracking, there are two main problems. Firstly, a low altitude leads to more ground obstructions which can induce a more significant initial state error in the filtering process. Secondly, LST tends to have a maneuvering system model, which can induce a greater difficulty in matching the actual LST model with the filtering model. To tackle the first problem, we transfer the original measurement update process in CKF to an iterative version using Levenberg-Marquardt (L-M) method and thus reduce the influence of the large initial filtering state error. Here, we call the new filtering algorithm L-MCKF. To tackle the second problem, we use Interacting Multiple Model (IMM) to generate a hybrid system to better match the actual LST trace. Finally, we use a simulation to test the availability of our proposed IMML-MCKF algorithm.