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和检测问题非常具有挑战性，最近受到了极大的关注。最近，提出了采用三次球基体积规则的 Cubature Kalman-multi-Bernoulli 滤波器来处理非线性模型。Cubature Kalman 滤波器在数学方面更具原则性和准确性。此外，最近提出了一种基于变分贝叶斯近似的多伯努利滤波器，用于估计测量方差的波动。然而，由于未知的检测概率，Cubature Kalman 和变分贝叶斯-多伯努利滤波器不适用于跟踪微型无人机。据我们所知，检测前跟踪（TBD）方案是跟踪小物体的有效方法。在这项工作中，提出了一种具有变分贝叶斯-TBD 的新型鲁棒 Cubature Kalman-Multi-Bernoulli 滤波器，并结合估计测量的波动方差。改进的滤波器是解决微型无人机探测轮廓估计问题的有效方法。提出了一种具有非线性 Cubature Kalman Gaussian 混合和逆 Gamma 近似的新颖实现，以估计微型无人机的混合运动学状态。仿真结果证实了所提出算法的有效性和鲁棒性。改进的滤波器是解决微型无人机探测轮廓估计问题的有效方法。提出了一种具有非线性 Cubature Kalman Gaussian 混合和逆 Gamma 近似的新颖实现，以估计微型无人机的混合运动学状态。仿真结果证实了所提出算法的有效性和鲁棒性。改进的滤波器是解决微型无人机探测轮廓估计问题的有效方法。提出了一种具有非线性 Cubature Kalman Gaussian 混合和逆 Gamma 近似的新颖实现，以估计微型无人机的混合运动学状态。仿真结果证实了所提出算法的有效性和鲁棒性。