Target differentiation with simple infrared sensors using statistical pattern recognition techniques

This study compares the performances of various statistical pattern recognition techniques for the differentiation of commonly encountered features in indoor environments, possibly with different surface properties, using simple infrared (IR) sensors. The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting feature in a way that cannot be represented by a simple analytical relationship, therefore complicating the differentiation process. We construct feature vectors based on the parameters of angular IR intensity scans from different targets to determine their geometry and/or surface type. Mixture of normals classifier with three components correctly differentiates three types of geometries with different surface properties, resulting in the best performance (100%) in geometry differentiation. Parametric differentiation correctly identifies six different surface types of the same planar geometry, resulting in the best surface differentiation rate (100%). However, this rate is not maintained with the inclusion of more surfaces. The results indicate that the geometrical properties of the targets are more distinctive than their surface properties, and surface recognition is the limiting factor in differentiation. The results demonstrate that simple IR sensors, when coupled with appropriate processing and recognition techniques, can be used to extract substantially more information than such devices are commonly employed for.     

LTN-72惯导设备在空间遥感器航空校飞中的应用

介绍了一种用于空间遥感器航空校飞的LTN-72惯导参数采集与传输装置。该装置能模拟星上数据管理系统(OBDH)传递包括校飞时间和全部LTN-72惯导参数在内的辅助数据,并具有输出检测信号和自检显示功能。装置经实际校飞使用,效果良好。     

应用遥感图像分析九江瑞昌地区构造与金铜成矿的关系

九瑞地区是长江中下游重要的金铜成矿区,遥感图像分析认为,北东东向断裂是主要的控矿构造,与北西向断裂的交汇部位是金铜成矿的有利地段。此外,环形构造又是另外一种控矿构造,目前所发现的金铜矿床均有物化探异常显示,并形成于环形构造的边缘。     

植被散射实验数据的特性分析

本文根据电波所获取的各种樾 射实测数据，分析了它们对不同极化波的响应特性。     

智能结构系统中的光纤传感技术

智能结构系统具有类似人体运动控制功能，埋置在工程结构或材料中便能获得顺应环境变化的自判断性、自适应性、自诊断性、自修复性等诸多性能。这一神奇的科学技术具有重大科学意义和广阔的应用前景。利用特性优良的光纤传感器可以构成一种特殊的光纤智能结构系统。本文较深入介绍适合智能结构系统的光纤多点式和分布式传感技术的原理、结构和实施方法。     

Compressive sensing SAR range compression with chirp scaling principle

Compressive sensing(CS) techniques offer a framework for the detection and allocation of sparse signal with a reduced number of measurements.This paper proposes a novel SAR range compression,namely compressive sensing with chirp scaling(CS-CS),achieving the same range resolution as conventional SAR approach,while using fewer range samplings.In order to realize accurate range cell migration correction(RCMC),chirp scaling principle is used to construct reference matrix for compressive sensing recovery.Additionally,error diagrams are designed for measurement of the performance of CS-CS,and some experiments of using real data are performed to deal with the errors caused by three conditions:SNR,sparsity and sampling.     

Multi-channel SAR imaging based on distributed compressive sensing

The rapid development of compressive sensing(CS)shows that it is possible to recover a sparse signal from very limited measurements.Synthetic aperture radar(SAR)imaging based on CS can reconstruct the target scene with a reduced number of collected samples by solving an optimization problem.For multi-channel SAR imaging based on CS,each channel requires sufficient samples for separate imaging and the total number of samples could still be large.We propose an imaging algorithm based on distributed compressive sensing(DCS)that reconstructs scenes jointly under multiple channels.Multi-channel SAR imaging based on DCS not only exploits the sparsity of the target scene,but also exploits the correlation among channels.It requires significantly fewer samples than multi-channel SAR imaging based on CS.If multiple channels offer different sampling rates,DCS joint processing can reconstruct target scenes with a much more flexible allocation of the number of measurements offered by each channel than that used in separate CS processing.