ID 原文 译文
22625 该文结合核相关滤波器(KCF)将多个核相关分类器通过集成学习整合到一个框架中。 In this paper, Kernelized Correlation Filters (KCF) tracking algorithm is used to integrate kernelized correlation classifiers into one framework through ensemble learning.
22626 利用 KCF 分类器具有解析解的特点平衡跟踪鲁棒性与实时性之间的矛盾，从而解决单个分类器无法处理复杂背景与显著的外观变化问题，并显著提升目标跟踪的性能与稳定性。 It uses the KCF classifier that has analytical solutions to balance the contradiction between the robustness and instantaneity, thereby addressing the complex background and significant appearance changes, and consequently significantly improving the tracking performance and stability.
22627 为了验证算法的有效性，该文利用两个核相关跟踪器联合学习出1 个强分类器。大量的定性定量实验表明所提的算法的跟踪性能超过传统的 KCF 算法，且跟踪速度也超过大多数比较算法。 To verify the effectiveness of the algorithm, this paper uses two kernelized correlation trackers to learn a strong classifier. The qualitative and quantitative experiments show that the proposed algorithm outperforms the traditional KCF algorithm, and the tracking speed is superior to most of the comparison algorithms.
22628 该文针对分布式 MIMO 雷达系统中的运动目标定位问题，以双基地距离(BR)及其变化率(BRR)作为观测量，提出一种基于多步加权最小二乘的代数解算法。 To solve the moving target localization problem in distributed MIMO radar systems, with the Bistatic Range (BR) and Bistatic Range Rate (BRR) used as the measurements, an algebraic algorithm based on multi-stage Weighted Least Squares (WLS) is proposed.
22629 算法共需要 3 步加权最小二乘估计。 The proposed algorithm needs three WLS stages.
22630 首先，在第 1 步加权最小二乘估计中，通过选取适当的辅助参数，将非线性的 BR 和 BRR 的观测方程进行伪线性化处理，从而得到目标位置和速度的粗略解； In the first WLS stage, by introducing proper additional parameters, the BR and BRR measurement equations are linearized, and weighted least square estimator is used to produce a rough estimate of target position and velocity.
22631 而后在后两步加权最小二乘估计中，利用目标位置参数和辅助参数之间的约束关系构建方程，从而得到目标位置和速度的精确估计。 Then in the latter two WLS stages, the relation between the target location parameters and additional parameters is utilized to refine the estimate.
22632 最后，推导了算法的理论误差，从理论上证明了算法可以达到克拉美罗界。 Finally, the theoretical error of the proposed algorithm is derived, and it is proved that the theoretical error attains the Cramer-Rao Lower Bound.
22633 在仿真实验中，将所提算法与现有算法进行了对比，验证了算法的优越性。 Simulation results indicate that the proposed algorithm achieves a significant performance improvement over the existing algorithms.
22634 该文提出一种新的同时具有高重复频率和大带宽性能的相干激光雷达系统。 A novel coherent ladar system with high repetition and wide bandwidth is proposed.