ID	原文	译文
8434	采用混沌理论优化粒子群算法的飞行参数,设计递减的动态惯性权重,以及引入遗传算法中的交叉、变异操作,使得算法能够快速收敛,并跳出局部最优实现全局最优。	Flight parameters of particle swarm optimization (pso) algorithm was optimized by using chaos theory, the design of diminishing dynamic inertia weight, as well as introducing the crossover and mutation in the genetic algorithm, makes the algorithm can fast convergence, and jump out of local optimal realize global optimal.
8435	在智能算法的框架下,提出一种启发式的任务交错算法,使得雷达任务中等待期的时间资源进一步得到利用。	In the framework of intelligent algorithm, presents a heuristic task interleaving algorithm, makes the radar task waiting period of time has been further utilization of resources.
8436	仿真结果表明,相比于遗传算法,所提算法的收敛速度更快,结果更优;	The simulation results show that compared with genetic algorithm, the proposed algorithm's convergence speed is faster, better results.
8437	相比于传统的启发式算法,所提算法的调度成功率提升了42%,时间利用率提升了40%,实现价值率提升了33%,时间偏移率减少了73%。	Compared with traditional heuristic algorithm, the proposed algorithm improved the scheduling success ratio of 42%, utilization rate of time increased by 40%, to achieve value rate is increased by 33%, time migration rate decreased by 73%.
8438	在短码直扩信号伪码序列的估计中,当使用特征值分解(eigenvalue decomposition,EVD)算法、奇异值分解(singular value decomposition,SVD)算法和压缩投影逼近子空间跟踪(projection approximation subspace tracking with deflation,PASTd)算法来估计伪码序列时,存在着当最大特征值和次大特征值相近时最大特征向量会受到干扰,进而影响伪码序列估计的问题。	In a short code in the estimation of pn code sequence spread spectrum signal, when using the eigenvalue decomposition (eigenvalue decomposition, EVD) algorithm, the singular value decomposition (singular value decomposition, SVD) algorithm and the compressing projection approximation subspace tracking (the projection approximation subspace tracking with deflation, PASTd) algorithm to estimate the pn code sequence, when the largest eigenvalue and large eigenvalues when close to the largest eigenvector can be disturbed, will affect the problem of pn code sequence estimation.
8439	针对此问题,提出了一种基于正交特性的伪码序列估计算法。	Aiming at this problem, proposed a pn code sequence estimation algorithm based on orthogonal characteristics.
8440	在已知码片速率和伪码周期的前提下,该算法首先把接收信号划分成长度为两倍码元宽度、数据重叠50%的数据段,然后用SVD估计出最大特征向量和次大特征向量。	In known code rate and under the premise of pn code period, the algorithm first divides the received signal growth degree is two times the element width, overlapping data 50% of data segment, and then use SVD estimate the maximum vector feature vector and great.
8441	由于最大特征向量和次大特征向量是相互正交的,可以利用两者的正交特性来估计扩频序列。	Because the largest eigenvector and large feature vector are orthogonal to each other, can make use of two orthogonal characteristics to estimate spread spectrum sequence.
8442	该算法不但能在信号失步时间未知的情况下估计伪码序列,而且仿真结果表明该算法具有稳定性高,需要的数据量少和能在低信噪比下有较好的估计性能等优点。	The algorithm can not only in the case of out-of-step time unknown to estimate pn code sequence, and the simulation results show that the algorithm has high stability, and need less amount of data and can be has good estimation performance under low SNR, etc.
8443	如何构造鲁棒的分类器一直是基于判别式的目标跟踪算法研究的热点,近些年多核学习通过线性组合多个核分类器达到了更好的分类性能,受到了广泛的关注。	How to construct robust classifier has been a hotspot of research on target tracking algorithm based on discriminant, multi-core study in recent years by linear combination of multiple classifiers achieve better classification performance, has received the widespread attention.