基于小波变换和神经网络的雷达滤波器故障诊断

由于模拟电路的非线性、容差性及元器件参数的连续可变性等特点的存在,传统的模拟电路故障诊断手段在实际运用中已经很难得到令人满意的结果。本文将小波变换与神经网络结合,对特征提取进行优化,以雷达滤波电路为研究对象,在考虑容差性的情况下对电路进行故障诊断,体现出小波神经网络在诊断正确性及时效性上所具有的优势。

一种简单的适用于警戒雷达的AMTD系统

本文介绍了一种AMTD系统,它的多路滤波器用加权DFT实现,并由杂波参数控制,它有多种工作模式。该系统具有简单、经济、易于实现、性能良好等优点,尤其适用于对老警戒雷达的改造。

一种新颖的基于低通控制特性的AFC系统

提出了一种新颖的基于低通滤波控制特性的 AFC系统 ,使用低通滤波器的过渡带代替传统的中频鉴频器的鉴频特性曲线 ,将由于各种因素造成发射机频率不稳的频率偏差转化为符号函数 ,结合 DDS技术 ,从而形成一种宽频率跟踪范围的

Designing and implementation of variance-dependent Goldstein radar interferogram filtering

The variance-dependent Goldstein radar interferogram filter takes into account the information of both interferometric coherence and multilook factors,and can produce very consistent results for interferograms generated under a wide variety of multilook factors and with very different noise level.However,the filter is a bit complicated and its application is still very limited.We present the designing and implementation of the variance-dependent Goldstein radar interferogram filtering,emphasizing on the logic flow,the generation of look-up table,the determination of filtering parameter,and the handling of edge information loss.Experiments with real interferograms are provided to demonstrate the applications of the designed filtering.Comparisons with the result of the coherence-dependent Goldstein filter show that improvements from 18.4% to 36.9% are achieved when the variance-dependent filter is used,and the noisier the interferogram,the greater the improvement.

Segments-based progressive TIN densification filter for DTM generation from airborne LIDAR data

Airborne light detection and ranging( LIDAR) has revolutionized conventional methods for digital terrain models( DTMs) acquisition. Ground filtering for airborne LIDAR is one of the core steps taken to obtain a high quality DTM. This paper presents a segments-based progressive TIN( triangulated irregular network) densification( SPTD) filter that can automatically separate ground points from non-ground points. The SPTD method is composed of two key steps: point cloud segmentation and clustering by iterative judgement. The clustering method uses the dual distance to obtain a set of seed points as a coarse spatial clustering process. Then the rest of the valid point clouds are classified iteratively. Finally,the datasets provided by ISPRS are utilized to test the filtering performance.In comparison with the commercial software Terra Solid,the experimental results show that the SPTD method in this paper can avoid single threshold restrictions. The expected accuracy of ground point determination is capable of producing reliable DTMs in the discontinuous areas.

APULSECOMPRESSORIMPLEMENTATIONWITHDSPFORSMALLTBPRODUCTLFMWAVEFORM

This paper describes a pulse compressor implementation with DSP for small Time Bandwidth (TB) product Linear Frequency Modulation (LFM) waveform. It contains the digital generation of the LFM waveform and the digital internally Hamming weighted compression filter. Two methods for suppression of time sidelobe of the digital pulse compressor are employed. First, the LFM waveform is modified by using cubic phase pre distortion for reducing the effect of Fresnel ripples in small TB product LFM waveform. Secondly, anti aliasing filter is used before A/D converter for reducing spectrum skirt level of the returned LFM waveform. The parameters of the compression filter implemented with IMSA100 DSP are programmable. The experiments show that the peak time sidelobe level of the digital pulse compressor is less than -32 dB for TB product of 20.

InSAR Kalman Filter Phase Unwrapping Algorithm Based on SRTM DEM

PU （phase unwrapping） is the key step and important problem in DEM （digital elevation model） extraction and the measurement of surface deformation of InSAR （Interferometric synthetic aperture radar）. The CKFPUA （conventional Kalman filter phase unwrapping algorithm） can obtain reliable results in the flat terrain areas, but it caused error transmission not making the accurate inversion of surface deformation information in the steep terrain. Considering this situation, so it needs to introduce topographic information for guiding phase unwrapping. Here the 90 m resolution DEM data have been used and it is obtained by SRTM （shuttle radar topography mission） measured jointly by NASA （National Aeronautics and Space Administration） and NIMA （National Imaging Mapping Agency） of U.S. Department of Defense. This paper presents a SD-KFPUA （Kalman filter phase unwrapping algorithm） based on SRTM DEM. With SRTM DEM directing InSAR image to implement phase unwrapping, the speed and accuracy are improved. By analyzing with the conventional Kalman filter phase unwrapping algorithms, it is shown that the proposed method can achieve good results in particular to improve unwrapping accuracy in the low coherence region.

Distance-Limited Filter for Extracting Ground Points

The extraction of points on the bare earth from point clouds acquired by airborne laser scanning is one of the most important steps for the generation of digital terrain models （DTM）. This process is called ＂filtering＂. However, most of the cur- rent filters erode the bare earth in steep sloped landscapes and at discontinuities, and they retain low vegetation. Therefore, a new filtering method for extracting ground points based on a distance limit is proposed in this paper. The angle criterion is used to assure the robustness of the algorithm. The experimental results show that the proposed filtering method can effectively derive the ground points from point clouds in complex urban areas.