产业区"环节建筑"城市化——以武烟集团综合科技大楼设计为例

该文分析了产业区的概念及现状，论述了环节建筑设计对整合产业区空间，分担城市职能，塑造个性化区段的作用。阐述了产业区环节建筑职能城市化，空间一体化，形式现代和生态化的设计发展趋势。以武烟集团综合科技大楼为例，进行了论证。     

低重频采样SAR系统中地面运动目标参数估计

低脉冲重复频率(pulse repetition frequency,PRF)采样合成孔径雷达(synthetic aperture radar,SAR)系统中运动目标回波信号存在Doppler谱模糊和Doppler中心频率模糊,这给运动目标参数估计带来了很大困难.由于杂波相消后的运动目标可以看作空间稀疏信号,基于压缩感知理论,本文提出一种低PRF采样SAR系统中的运动目标参数估计的新方法.首先采用基于Keystone变换的稀疏走动校正方法来实现包络走动校正和估计出引起整数倍PRF Doppler频率偏移的垂直航向速度分量,利用压缩感知(compressed sensing,CS)理论进行稀疏信号重建,将Doppler谱模糊的运动目标参数估计问题转化为求解优化方程稀疏解,最后利用优化方法获得运动目标的速度以及方位位置.仿真实验和实测数据都验证了本文方法的有效性.     

Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability

The lack of maps depicting forest three-dimensional structure, particularly as pertaining to snags and understory shrub species distribution, is a major limitation for managing wildlife habitat in forests. Developing new techniques to remotely map snags and understory shrubs is therefore an important need. To address this, we first evaluated the use of LiDAR data for mapping the presence/absence of understory shrub species and different snag diameter classes important for birds (i.e. ≥ 15 cm, ≥ 25 cm and ≥ 30 cm) in a 30,000 ha mixed-conifer forest in Northern Idaho (USA). We used forest inventory plots, LiDAR-derived metrics, and the Random Forest algorithm to achieve classification accuracies of 83% for the understory shrubs and 86% to 88% for the different snag diameter classes. Second, we evaluated the use of LiDAR data for mapping wildlife habitat suitability using four avian species (one flycatcher and three woodpeckers) as case studies. For this, we integrated LiDAR-derived products of forest structure with available models of habitat suitability to derive a variety of species-habitat associations (and therefore habitat suitability patterns) across the study area. We found that the value of LiDAR resided in the ability to quantify 1) ecological variables that are known to influence the distribution of understory vegetation and snags, such as canopy cover, topography, and forest succession, and 2) direct structural metrics that indicate or suggest the presence of shrubs and snags, such as the percent of vegetation returns in the lower strata of the canopy (for the shrubs) and the vertical heterogeneity of the forest canopy (for the snags). When applied to wildlife habitat assessment, these new LiDAR-based maps refined habitat predictions in ways not previously attainable using other remote sensing technologies. This study highlights new value of LiDAR in characterizing key forest structure components important for wildlife, and warrants further applications to other forested environments and wildlife species.     

Migration compensation algorithm for maneuvering target in passive radar based on FRT-MLVD

During the long coherent integration time in passive radar,the motion parameters (such as high speed,acceleration and jerk motion,etc.) will bring about range migration (RM) and Doppler frequency migration (DFM),further deteriorate the integration performance.To realize the coherent integration of maneuvering targets with jerk motion,a method based on frequency reversing transform (FRT) and modified Lv’s distribution (MLVD) called FRT-MLVD was proposed to achieve the coherent integration and motion parameters estimation.More specifically,the FRT was firstly proposed to remove RM.Then the MLVD was employed to estimate the acceleration and jerk parameters.After compensating the DFM induced by the acceleration and jerk motion,the residual RM was corrected and the velocity and range was achieved via the KT operation.Simulation results demonstrate that the proposed method can effectively compensate the RM and DFM induced by the target motion parameters in passive radar,and for maneuvering targets with jerk motion,the proposed method achieves a better integration and detection performance over existing methods.     

基于Keystone变换的相参积累方法

由于传统脉冲雷达回波信号因为各种原因会出现距离走动问题,为了校准距离走动,通过分析回波信号相参积累的理论知识,介绍了实现Keystone变换的三种方法:离散傅里叶变换(DFT)+ IFFT算法、Sinc内插法、ChirpZ变换(CZT)法的原理,并提出了基于Keystone变换的相参积累方法,用Matlab平台证实了该方法能有效校准距离走动使得雷达高度表检测更为准确,并且通过实验验证了这种方法的可行性与准确性.     

基于STAP的机载雷达高速运动目标检测技术研究

针对机载雷达高速运动目标检测中存在严重的距离单元走动问题,将Keystone变换与STAP技术结合,提出了一种目标检测方法。该方法首先将雷达接收到的回波数据变换到频域,然后利用Keystone变换对目标的距离走动进行校正,再将校正后的数据变换回时域并做空时自适应处理（STAP）。仿真结果表明,该方法可有效克服高速运动目标距离走动导致STAP处理性能下降的问题,改善了目标检测性能。     

Parameter estimation of moving targets in the SAR system with a low PRF sampling rate

In the synthetic aperture radar(SAR)system with low pulse repetition frequency(PRF)sampling,it is difficult for the motion parameters estimation of the moving targets,because of the Doppler spectrum ambiguity and Doppler centroid frequency ambiguity of the echo signals.Considering that moving targets are sparsely distributed in the observed scene,their positions and velocities can be reconstructed by using the compressed sensing(CS)technique.In this paper,the range-walk correction are implemented by the Keystone transform and the sparse range-walk correction(SRWC),then the CS technique is proposed to reconstruct motion parameters by processing the azimuth signals of the moving targets.Experiments using the simulated and real data are performed,and the results confirm the validity of the proposed method.     

一种多载频MIMO雷达高速运动目标多维参数估计方法

 多载频MIMO雷达中,高速运动目标回波信号经通道分离后各通道的距离和多普勒频率均不在同一分辨单元,无法利用传统的超分辨算法对目标距离、角度等参数进行估计.本文根据目标回波特点提出一种基于级联Keystone变换的高速运动目标参数估计方法.该方法先在快时间维利用Keystone变换校正距离走动,再在慢时间维进行Keystone变换校正多普勒走动,最后用MUSIC算法进行距离、方位和俯仰等参数估计.仿真结果表明了所提方法的可行性和有效性.     

一种用于密集强弱目标速度高分辨估计的IAA-MCapon算法

由于分辨精度有限以及易受目标能量强弱的影响,基于Fast Fourier Transform(FFT)的算法不能对位于同一距离单元的密集强弱目标进行有效的速度估计.基于此,本文采用基于协方差矩阵迭代自适应(Iterative Adaptive Algorithm,IAA)的改进Capon(Modified Capon,MCapon)算法对密集强弱目标速度参数进行高分辨估计.该方法首先采用Keystone变换进行距离走动校正,然后利用目标所在的距离单元数据进行协方差矩阵重构,接着利用MCapon方法使得密集强弱目标信号幅度输出均为常数1,最后实现了速度的高分辨估计,在保持高分辨的同时提高了稳健性.理论分析和实验仿真结果表明,所提方法可对包络校正后位于同一距离单元的密集强弱目标径向速度参数进行有效的高分辨估计,估计性能优于FFT类方法及子空间投影方法.