Radar sensor network for target detection using Chernoff information and relative entropy

In this paper, we propose to apply information theory to Ultra wide band (UWB) radar sensor network (RSN) to detect target in foliage environment. Information theoretic algorithms such as Maximum entropy method (MEM) and mutual information are proven methods, that can be applied to data collected by various sensors. However, the complexity of the environment poses uncertainty in fusion center. Chernoff information provides the best error exponent of detection in Bayesian environment. In this paper, we consider the target detection as binary hypothesis testing and use Chernoff information as sensor selection criterion, which significantly reduces the processing load. Another strong information theoretic algorithm, method of types, is applicable to our MEM based target detection algorithm as entropy is dependent on the empirical distribution only. Method of types analyzes the probability of a sequence based on empirical distribution. Based on this, we can find the bound on probability of detection. We also propose to use Relative entropy based processing in the fusion center based on method of types and Chernoff Stein Lemma. We study the required quantization level and number of nodes in gaining the best error exponent. The performance of the algorithms were evaluated, based on real world data.     

The radar method: an effective line search for piecewise linear concave functions

The maximization of one-dimensional piecewise linear concave (OPLC) functions arises in the line search associated with the maximization of piecewise linear concave functions (e.g. Kelley cutting plane method). The OPLC line search is usually done by the next-break-point method, where one goes from break point to break point up to the optimum. If the number of break points is large this method will be computationally expensive. One can also use some classical derivative-free line search method as for example the golden section method. Such methods do not take advantage of the OPLC geometry. As an alternative, we propose an improved version of the so-called radar method, which maximizes an OPLC function by maximizing successive outer approximations. We prove superlinear and finite convergence of the radar method. Furthermore, our computational test shows that the radar method is highly effective independently from the number of break points.     

A device to measure wheel slip to improve the fuel efficiency of off road vehicles

A hall sensor based simple technique was introduced to measure wheel slip and a microcontroller based embedded digital system was developed to display wheel slip data and warn the operator with audible and visible warnings if the optimum range is exceeds. Hall sensor slip measurement system was validated in controlled soil bin condition, tar macadam surface and actual field condition and compared with the commercial radar sensor. The developed system is simple in construction and can be mounted to any make and model of agricultural tractors by entering the appropriate rolling radius via the computer interface. Field trials were conducted to measure wheel slip and fuel consumption on farm use with and without activation of slip indicator; it was observed that, the amount of fuel saving during various agricultural operation was up 1.3 l/h.     

Estimation of vertical wind velocity using doppler radar data with vorticity constraints

The vorticity equation and the mass continuity equation are used as constraints to aid in calculation of the vertical component of a wind field from horizontal wind components. Typically the horizontal wind components result from estimations obtained from radar data. Using a Hilbert space minimization formulation, we characterize the estimated vertical velocity as a solution of an elliptic boundary value problem whose coefficients are functions of the horizontal wind components. Differentiable dependence of the vertical component of the wind field with respect to the horizontal fields is established. Finite dimensional approximating problems are obtained. A numerical study is presented using a sample problem based on the Beltrami flow to compare accuracy of the estimated vertical wind component with the exact. Also, sensitivity to perturbations in horizontal wind components are observed.     

半正弦波相关型三维激光雷达

提出了基于半正弦波-方波相关法的凝视成像三维激光雷达.用傅里叶级数展开对新方法进行了分析.理论分析表明,半正弦-方波相关可以在抑制高频噪音的同时加大调制的交流分量.基于新相关方法的探测系统可以在不损失测距准确度的条件下可以获得更大的输出光功率从而获得更大的探测距离.采用基于新方法的探测装置对~70 m外约100 m2的目标进行了探测实验.实验结果表明,基于新方法的激光雷达在60 m处的分辨率约为0.3 m,从而验证了理论分析的结论.     

Microwave and Millimeter Wave Characteristics and Attenuation of Clouds over some Malaysian Equatorial Stations

Based on radar range height indicator (RHI) measurements, cloud characteristics in relation to radiowave propagation over three locations in different geographical region in western Malaysia have been presented. It is seen that low cloud occurrence over these locations are quite significant. Cloud attenuation and noise temperature can result in serious degradation of telecommunication link performances. This paper presents cloud coverage in different months, 0°C isotherm height and cloud attenuation results at 12 GHz, 20 GHz, 36 GHz, 50 GHz, 70 GHz and 100 GHz over measurement site. The low level cloud over the measurement sites has been found to occur for many days and nights and particularly in the months of April to May and October to December. Such results are useful for satellite communication and remote sensing application in Malaysia.     

Frequency Sources in W-band Radar Front-end with Low Phase Noise

A W-band coherent stepped-frequency pulsed radar front-end is developed. It consists of a millimetre wave transmitting source, a mm-wave local source, a DDS with multi frequency points output and two microwave sources serving as local oscillators. All the sources are coherent with the 120 MHz referenced crystal oscillator. The mm-wave sources are realized by frequency multiplier chain, up-conversion and injection locking. The phase noise of fundamental-wave injection-locked W-band harmonic Gunn oscillator output signal achieves −98 dBc/Hz at 10 kHz offset and the spurious output is less than −50 dBc. The received intermediate frequency signal is also presented.     

185雷达标校测量电视定线望远镜的校调

雷达与标校电视定线望远镜的组合,实际上即成为雷达经纬仪,见图1所示,但是其中定线望远镜与一般大型经纬仪中的望远镜工作情况有所不同。区别如下:其一、定线望远镜在雷达上的安装位置与雷达电轴x轴之间有一偏移距离-ΔY和ΔZ。     

Identification of rain cells from radar and stochastic modelling of space-time rainfall

We discuss two problems related to the utilization of weather radar: the automated identification of rain cells and the extension of cluster models to include the random variability of space-time rainfall within and between cells. The need for such extension emerges from visual inspection and formal analysis of radar reflectivity images. The algorithm proposed for the identification of cells is based on statistical techniques for the estimation of probability density mixtures. The algorithm does not assign pixels to cells deterministically; rather, it calculates the probability with which each pixel belongs to the different cells. Through an iterative procedure, the cell parameters and pixel probabilities are updated until the final identification of cells is reached. The second part of the paper deals with a generalization of cluster rainfall models in space and time. The models studied here combine an arbitrary birth point process with arbitrary random fields generated by the cells. Second-moment properties of these processes are derived.

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Sommario Vengono descritti i primi risulati di un lavoro in corso su due problemi legati all'uso del radar meteorologico: l'identificazione automatica delle celle di pioggia e l'estensione dei modelli a cluster per includere la variabilità casuale delle precipitazioni nello spazio e nel tempo all'interno e fra le celle. La necessità di tale estensione sorge sia dall'esame visivo, sia da un'analisi formale delle immagini della riflettività radar. L'algoritmo proposto per l'identificazione delle celle è basato sulle tecniche statistiche per la stima delle miscele di distribuzioni di densità di probabilità. L'algoritmo non assegna in maniera deterministica i singoli pixels alle celle, bensì calcola la probabilità con cui ogni pixel appartiene alle diverse celle. Attraverso una procedura iterativa si calcolano di volta in volta i parametri delle celle e le probabilità dei pixels, fino a che si raggiunge un assetto finale e le celle vengono identificate. Nella seconda parte del lavoro si tratta della generalizzazione dei modelli a cluster nello spazio e nel tempo. I modelli qui studiati combinano un processo arbitrario di occorrenza delle celle con un campo casuale arbitrario generato dalle celle. In particolare, sono derivate le proprietà generali dei secondi momenti di tali processi.