ID 原文 译文
10294 最后,结合自适应渐消卡尔曼滤波(adaptive fading Kalman filter,AFKF)的思想,提出了IMAM-AFAKF算法。 ‭Finally, combined with the adaptive fading Kalman filter, the adaptive fading Kalman filter, AFKF) thoughts, IMAM - AFAKF algorithm is proposed.
10295 仿真结果表明,无论是强机动还是弱机动,IMAM-AFAKF算法都具有较好的跟踪性能。 ‭The simulation results show that both strong mobility and weak maneuvering, IMAM - AFAKF algorithm has good tracking performance.
10296 多波段信号融合技术在信号层将多个不同子带融合成一个大带宽信号,因而能够有效提高雷达图像距离分辨率。 Multiband signal fusion technology in the signal will be different subband merging into a large bandwidth signal, therefore can effectively improve the range resolution radar images.
10297 目前,基于全极点模型的融合技术主要采用root-MUSIC(multiple signal classification)及其改进算法实现极点的估计,在较弱的噪声条件下这种方法得到了不错的融合效果。 At present, the fusion technology based on full pole model mainly adopts the root - MUSIC (multiple signal classification) and its improved algorithm to realize the extreme estimates, under the condition of weak noise this method get good fusion effect.
10298 然而在低信噪比条件下root-MUSIC算法容易受到噪声干扰而难以实现正确极点获取,进而极大影响到最终信号融合效果。 However, under the condition of low SNR root - MUSIC algorithm is susceptible to noise and difficult to achieve the correct pole, which greatly affect the final signal fusion effect.
10299 为减小噪声影响,提出用矩阵束算法实现多波段信号极点估计。 Beam to reduce noise influence, using matrix estimation algorithm to achieve multichannel signal pole.
10300 在此基础上通过不同子带对应极点间的相位关系估计出相干参数,同时对融合结果以信号差的2范数最小为准则进行迭代,以减小融合信号的误差。 On this basis, through the phase relationship between different subband corresponding to the pole estimate the coherent parameter, at the same time, the result of the fusion rule of the minimum 2 norm of poor signal as the iteration, as to reduce the error of fusion signal.
10301 最后采用加权寻优的方式进一步提高了信号的融合精度。 Finally using weighted optimization way to further improve the fusion precision of the signal.
10302 仿真实验结果表明,提出的方法有效提高了低信噪比条件下的多波段信号融合效果。 The simulation results show that the proposed method effectively improves the low SNR of multiband signal fusion effect.
10303 为进一步减小收敛速率与稳态误差之间的矛盾,改善自适应滤波算法,利用改进的Lorentzian函数提出了一种新的变步长凸组合最小均方(new variable step-size convex-combination of least mean square,NVSCLMS)算法,该算法既有效提高了收敛速率又具备很好的抗干扰能力。 In order to further reduce the contradiction between convergence speed and steady-state error, improve the adaptive filtering algorithm, the use of the proposed a new improved Lorentzian function variable step convex combination least mean square (the new variable step - size convex - combination of further mean square, NVSCLMS) algorithm, the algorithm effectively improves the convergence rate and good anti-jamming ability.