ID 原文 译文
38556 通过仿真结果可以证明所提算法的有效性。 Through the simulation results can prove the effectiveness of the proposed algorithm.
38557 为提高弹载导引头成像精度,研究分析大斜视成像具有重大意义。 To improve the imaging precision of missile seeker, analysis large squint imaging is of great significance.
38558 针对传统wk算法在构造Stolt映射关系时未考虑等效速度变化以及进行方位校正时运算复杂等问题,提出基于改进wk算法的弹载合成孔径雷达斜视成像模型。 For traditional wk algorithm did not consider when constructing Stolt mapping relation a equivalent velocity change and azimuth correction complex operation and so on, is put forward based on improved strabismus wk algorithm of on-board, a synthetic aperture radar imaging model.
38559 首先,详细推导基于Stolt插值的wk算法,辨析在成像参数、多普勒中心校正和统一相位补偿等三个环节中易存在的混淆,为算法改进提供严谨模型。 First of all, is derived in detail based on Stolt interpolation wk algorithm, a discrimination in imaging parameters, doppler central school with uniform phase compensation three links such as easy of confusion, provides rigorous model algorithm is improved.
38560 然后,针对非参考点目标的等效速度随着距离向不断变化,构造新的Stolt映射关系减小残余相位误差。 Then, in view of the reference point target of equivalent velocity changing with distance to construct new Stolt mapping reduce the residual phase error.
38561 在此基础上,针对较难精确实现多个点目标的方位位置校正函数,通过引入参考目标点构造近似校正函数,避免进行复杂的二维插值或坐标转换。 On this basis, in view of the difficult to precisely implement multiple point target azimuth position correction function, by introducing the reference target to construct approximate correction function, avoid complex two-dimensional interpolation and coordinate transformation.
38562 最后,以大斜视成像为例,对多个点目标进行仿真,验证该算法的有效性。 Finally, by a large squint imaging as an example, the multiple point targets are simulated, verify the effectiveness of the proposed algorithm.
38563 针对认知无线电(cognitive radio,CR)宽带频谱检测过程中存在的采样压力大、数据传输量大、信道衰落严重等问题,提出了一种基于支撑集融合的分布式协作压缩频谱检测方法。 For cognitive radio, cognitive radio (CR) broadband spectrum in the process of testing the sample pressure, large amount of data transmission, the channel fading serious problems, this paper proposes a distributed collaboration based on support merging compression spectrum detection method.
38564 在该方法中,本地信号重构过程和频谱稀疏支撑集的分布式融合过程反复交替进行,将本地重构过程中获得的稀疏支撑集信息进行分布式融合,又将融合结果作为先验信息指导本地信号再次重构,多次重复以实现信号重构与频谱检测。 In this method, the local spectrum sparse signal reconstruction process and the support set alternately repeatedly distributed fusion process, will be obtained in the process of local reconstruction sparse support distributed set of information fusion, and the fusion results as a priori information to guide the local signal reconstruction again, repeatedly in order to realize the signal is reconstructed and spectrum detection.
38565 仿真结果表明,所提出方法的频谱检测性能可接近集中式的压缩检测方法,而该方法的迭代重构过程复杂度低,具有计算开销少的优势。 The simulation results show that the spectrum detection performance of the presented method can be close to the compression of the centralized detection method, and the method of low complexity iterative reconstruction process, with the advantages of less computational overhead.