ID	原文	译文
7584	仿真结果验证了过2采样DFT滤波器组结构的正确性,提出的震荡权重粒子群杂交滤波器设计可以精确地重构跨多个信道的宽频信号,具备干扰宽频信号的能力。	Over 2 sampling simulation results verified the correctness of the DFT filter bank structure and weights of shock was proposed hybrid filter design of pso can accurately reconstruct across multiple channels of broadband signal, have the ability to interfere with the broadband signal.
7585	传统目标跟踪算法首先通过采样信号估计时延或多普勒等参数,然后利用这些参数构成的跟踪方程获得目标运动轨迹,这种两步跟踪模式存在位置信息损失、误差累积等问题,跟踪精度仍有待提高。	Traditional target tracking algorithm firstly by the sampling signal to estimate time delay and doppler parameters, and then use these parameters constitute the track equation of target motion trajectory, the two step tracking model some problems such as location information loss, error accumulation, tracking accuracy remains to be improved.
7586	针对此问题,提出一种利用数据域采样信号,基于时延和多普勒信息的直接跟踪算法。	Aiming at this problem, a data domain sampling signal is used, based on time delay and doppler information of the tracking algorithm directly.
7587	该算法利用多个观测站的接收信号,首先建立一个基于连续时间和多普勒信息的直接跟踪模型;	Using multiple observatory of received signal, the algorithm first establish a directly based on continuous time and doppler information tracking model;
7588	然后基于进化粒子滤波算法,对所提跟踪模型进行迭代求解,提高算法计算效率,实现对运动目标的快速高精度跟踪;	Then based on evolutionary particle filter algorithm, the proposed iteration tracking model, improve the computational efficiency of the algorithm, realize the rapid and high precision of movement target tracking;
7589	最后,针对所提模型,推导了目标直接跟踪的克拉美罗下界(Cramer-Rao lower bound,CRLB)递归求解方法,给出了算法的跟踪误差下限。	Finally, in view of the proposed model, the target is deduced directly grams of Latin America, and lower bounds of the tracking (Cramer - Rao lower bound, the CRLB) recursive algorithm, the algorithm of tracking error threshold is given.
7590	仿真实验表明,与现有跟踪算法相比,所提算法跟踪精度更高,收敛速度更快,尤其在低信噪比条件下更能逼近CRLB。	Simulation experiments show that compared with the existing tracking algorithm, the proposed algorithm is higher tracking precision, faster convergence rate, especially under the condition of low SNR more approaching CRLB.
7591	针对1点随机抽样一致性(random sample consensus,RANSAC)单目视觉导航算法中的主动视觉匹配失效问题,提出了一种基于辅助匹配的1点RANSAC单目视觉导航算法。	1 point for random sampling consistency (the random sample consensus, RANSAC) monocular visual navigation algorithm of active visual matching failure problem, puts forward a 1 point based on auxiliary matching RANSAC monocular visual navigation algorithms.
7592	首先,该算法通过引入尺度不变特征变换(scale invariant feature transform,SIFT)算法完成特征匹配;	First, the algorithm by introducing a scale invariant feature transform (scale invariant feature transform, SIFT) feature matching algorithm is complete;
7593	其次,采用RANSAC算法解算基础矩阵和匹配点;	Secondly, use RANSAC algorithm based matching point matrix and calculating;