Barbary Mohamed, ElAzeem Mohamed H Abd
Department of Electrical Engineering, Alexandria University, Alexandria, Egypt; Technical Research and Developing Centre, Elsayeda Aisha, Cairo, Egypt.
Department of electronics and communication, Arab Academy for Science Technology and Maritime Transport, Egypt.
ISA Trans. 2021 Aug;114:277-290. doi: 10.1016/j.isatra.2020.12.042. Epub 2020 Dec 28.
The problem of nonlinear tracking and detection of small unmanned aerial vehicles and micro-drone targets is very challenging and has received great attention recently. Recently, the Cubature Kalman-multi-Bernoulli filter which employs a third-degree spherical-radical cubature rule has been presented to handle the nonlinear models. The Cubature Kalman filter is more principled and accurate in mathematical terms. In addition, a recent multi-Bernoulli filter based on variational Bayesian approximation has been presented with the estimation the fluctuation of variances of measurement. However, Cubature Kalman and variational Bayesian-Multi-Bernoulli filters are unsuitable for tracking the micro-drones because of the unknown probability of detection. As we known, the track-before-detect (TBD) schemes was an effective method for tracking the small objects. In this work, a novel robust Cubature Kalman-Multi-Bernoulli filter with variational Bayesian-TBD is proposed jointing with estimate the fluctuated variances of measurement. The improved filter is an effective method to solve the problem of detection profile estimation for micro-drones. A novel implementation with a non-linear Cubature Kalman Gaussian mixture and Inverse Gamma approximation is presented to estimate a hybrid kinematic state of micro-drones. The simulation results confirm the effectiveness and robustness of the proposed algorithm.
小型无人机和微型无人机目标的非线性跟踪与检测问题极具挑战性，且近年来备受关注。最近，已提出采用三阶球面 - 径向容积规则的容积卡尔曼 - 多贝努利滤波器来处理非线性模型。容积卡尔曼滤波器在数学上更具原理性且更为精确。此外，最近还提出了一种基于变分贝叶斯近似的多贝努利滤波器，用于估计测量方差的波动。然而，由于检测概率未知，容积卡尔曼滤波器和变分贝叶斯 - 多贝努利滤波器不适用于跟踪微型无人机。众所周知，先跟踪后检测（TBD）方案是跟踪小目标的有效方法。在这项工作中，提出了一种结合变分贝叶斯 - TBD并估计测量波动方差的新型鲁棒容积卡尔曼 - 多贝努利滤波器。改进后的滤波器是解决微型无人机检测轮廓估计问题的有效方法。提出了一种采用非线性容积卡尔曼高斯混合和逆伽马近似的新型实现方法，以估计微型无人机的混合运动状态。仿真结果证实了所提算法的有效性和鲁棒性。
