Super-resolution reconstruction of synthetic-aperture radar image using adaptive-threshold singular value decomposition technique

A super-resolution reconstruction approach of radar image using an adaptive-threshold singular value decomposition (SVD) technique was presented,and its performance was analyzed,compared and assessed detailedly.First,radar imaging model and super-resolution reconstruction mechanism were outlined.Then,the adaptive-threshold SVD super-resolution algorithm,and its two key aspects,namely the determination method of point spread function (PSF) matrix T and the selection scheme of singular value threshold,were presented.Finally,the super-resolution algorithm was demonstrated successfully using the measured synthetic-aperture radar (SAR) images,and a Monte Carlo assessment was carried out to evaluate the performance of the algorithm by using the input/output signal-to-noise ratio (SNR).Five versions of SVD algorithms,namely 1) using all singular values,2) using the top 80% singular values,3) using the top 50% singular values,4) using the top 20% singular values and 5) using singular values s such that s2≥max(s2)/rinSNR were tested.The experimental results indicate that when the singular value threshold is set as smax/(rinSNR)1/2,the super-resolution algorithm provides a good compromise between too much noise and too much bias and has good reconstruction results.

Accelerating BP-Based Iterative Low-Density Parity-Check Decoding by Modified Vertical and Horizontal Processes

Two modified BP algorithms related to vertical and horizontal processes are proposed to accelerate iterative low-density parity- check （LDPC） decoding over an additive white Gaussian noise （AWGN） channel, where the newly updated extrinsic information is immediately used in the current decoding round. Theoretical analysis and simulation results demonstrate that both the modified approaches provide significant performance improvements over the traditional BP algorithm with almost no additional decoding complexity. The proposed algorithm with modified horizontal process offers even better performance than another algorithm with the modified horizontal process. The two modified BP algorithms are very promising in practical communications since both can achieve an excellent trade-off between the performance and decoding complexity.

AN IMPROVED SAR-GMTI METHOD BASED ON EIGEN-DECOMPOSITION OF THE SAMPLE COVARIANCE MATRIX

An improved two-channel Synthetic Aperture Radar Ground Moving Target Indication (SAR-GMTI) method based on eigen-decomposition of the covariance matrix is investigated. Based on the joint Probability Density Function (PDF) of the Along-Track Interferometric (ATI) phase and the similarity between the two SAR complex images, a novel ellipse detector is presented and is applied to the indication of ground moving targets. We derive its statistics and analyze the performance of detection process in detail. Compared with the approach using the ATI phase, the ellipse detector has a better performance of detection in homogenous clutter. Numerical experiments on simulated data are presented to validate the improved performance of the ellipse detector with respect to the ATI phase approach. Finally, the detection capability of the proposed method is demonstrated by measured SAR data.

New band-notched UWB antenna

A simple and compact ultra wideband （UWB） printed monopole antenna with band-notched performance is proposed in this paper. The antenna is partially grounded so that the Q value is depressed and the impedance bandwidth is broadened. A small strip bar is loaded on each arm of the similar U-shaped radiator. The impedance bandwidth of the antenna overlap with IEEE 802.11a is rejected consequently. The geometry parameters of the antenna are investigated and optimized with HFSS. The measured bandwidth of the proposed antenna occupies about 7.89 GHz covering from 3.05 GHz to 10.94 GHz with expected notched band from 4.96 GHz to 5.98 GHz. A quasi-omnidirectional and quasi-symmetrical radiation pattern in the whole band is also obtained. As a result, a UWB wireless communication system can be simplified with the band-notched UWB antenna presented.

Phase-domain blind estimation of symbol duration based on Haar wavelet transform

A phase-domain blind estimator of symbol duration based on Haar wavelet transform（HWT） is proposed.It can estimate the symbol duration of phase modulated signals,such as M-ary phase-shift keying（MPSK） signals and polyphase coded signals.The closed form of the spectrum of HWT is derived.Theoretical analysis shows the frequency of the first spectral peak is equal to the symbol rate,which is the reciprocal of symbol duration.Thus the symbol duration can be extracted from the spectrum.Subsequently,the optimum wavelet scale is determined according to the maximum output signal to noise ratio（OSNR） criterion.MAT-LAB simulations show that this algorithm can blindly estimate the symbol duration without any prior knowledge.This estimator need not estimate the carrier frequency and has the characteristics of low computation complexity and high accuracy.

Intelligent Cost Modeling Based on Soft Computing for Avionics Systems

In parametric cost estimating, objections to using statistical Cost Estimating Relationships （CERs） and parametric models include problems of low statistical significance due to limited data points, biases in the underlying data, and lack of robustness. Soft Computing （SC） technologies are used for building intelligent cost models. The SC models are systemically evaluated based on their training and prediction of the historical cost data of airborne avionics systems. Results indicating the strengths and weakness of each model are presented. In general, the intelligent cost models have higher prediction precision, better data adaptability, and stronger self-learning capability than the regression CERs.

Design,implementation and evaluation of write-enabled CramFS

The compressed ready-only-memory （ROM） file system （CramFS） has been widely used in Linux-based devices. However, it is a read-only filesystem which can not meet the requirement of today＇s smart mobile devices because most of them require updating the software on the air （OTA）. This paper presents a design and implementation of write-enabled CramFS which only introduces minor architecture changes and very limited space filesystems also proves the feasibility of this solution. cost. The performance benchmark with other popular write-enabled

Multiple-target tracking with adaptive sampling intervals for phased-array radar

A novel adaptive sampling interval algorithm for multitarget tracking is presented. This algorithm which is based on interacting multiple models incorporates the grey relational grade （GRG） into the particle swarm optimization （PSO）. Firstly, the desired tracking accuracy is set for each target. Secondly, sampling intervals are selected as particles, and then the advantage of the GRG is taken as the measurement function for resource management. Meanwhile, the fitness value of the PSO is used to measure the difference between desired tracking accuracy and estimated tracking accuracy. Finally, it is suggested that the radar should track the target whose prediction value of the next sampling interval is the smallest. Simulations show that the proposed method improves both the tracking accuracy and tracking efficiency of the phased-array radar.

Density-based trajectory outlier detection algorithm

With the development of global position system（GPS）,wireless technology and location aware services,it is possible to collect a large quantity of trajectory data.In the field of data mining for moving objects,the problem of anomaly detection is a hot topic.Based on the development of anomalous trajectory detection of moving objects,this paper introduces the classical trajectory outlier detection（TRAOD） algorithm,and then proposes a density-based trajectory outlier detection（DBTOD） algorithm,which compensates the disadvantages of the TRAOD algorithm that it is unable to detect anomalous defects when the trajectory is local and dense.The results of employing the proposed algorithm to Elk1993 and Deer1995 datasets are also presented,which show the effectiveness of the algorithm.

IMAGE-BASED SCALING FOR SHIP TOP VIEW ISAR IMAGES

A high quality top view or side view ship ISAR image with proper cross-range scale is very useful for target recognition. A technique aiming at solving the ship top view image scaling is developed, in which the cross-range scale information is obtained by measuring the slopes of the two feature lines of the ship, the centerline and the stern line. Neither the prior knowledge about the ship nor the tracking data is required. The proposed technique is fully based on the image. It is used with ease and high efficiency. Examples are provided to demonstrate its effectiveness with both simulated and real data. The scaled results are in accordance with the real shape of the ship.

JOINT ITERATIVE DECODING FOR SIMPLE-ENCODING SYSTEMATIC IRREGULAR-LDPC-BASED CODED COOPERATION IN NON-IDEAL RELAY CHANNEL

In this paper, a new kind of simple-encoding irregular systematic LDPC codes suitable for one-relay coded cooperation is designed, where the proposed joint iterative decoding is effectively performed in the destination which is in accordance with the corresponding joint Tanner graph characterizing two different component LDPC codes used by the source and relay in ideal and non-ideal relay cooperations. The theoretical analysis and simulations show that the coded cooperation scheme obviously outperforms the coded non-cooperation one under the same code rate and decoding complex. The significant performance improvement can be virtually credited to the additional mutual exchange of the extrinsic information resulted by the LDPC code employed by the source and its counterpart used by the relay in both ideal and non-ideal cooperations.

Performance of multiuser CDMA system with space-time block coding in MIMO Rayleigh fading channels

In this paper, by introducing orthogonal space-time coding scheme, the multiuser CDMA systems with different space time codes are given, and corresponding system performance is investigated over Rayleigh fading channel. A low-complexity multiuser receiver scheme is developed for space-time coded CDMA systems. The scheme can make full use of the complex orthogonality of space-time coding to simplify the high decoding complexity of the existing scheme. Compared to the existing scheme with exponential decoding complexity, it has linear decoding complexity. Based on the performance analysis and mathematical calculation, average bit error rate （BER） of the system is derived in detail, and tight closed-form approximation expressions of BER are attained. Simulation results on average BER are in agreement with the theory analysis. The results show that the proposed scheme can achieve almost the same performance as the existing scheme. Moreover, on the condition of same system throughput and concatenation of channel code, the given full-rate space-time coded CDMA system has lower BER than the full-diversity space-time coded CDMA systems.

NEW RANGE ALIGNMENT ALGORITHM FOR ISAR BASED ON HIGH ORDER MOMENT

A new technique is proposed for range alignment in Inverse Synthetic Aperture Radar (ISAR). The basic idea is to perform range alignment using a maximum kurtosis (fourth-order central moment) criterion. After maximizing the kurtosis of the combined range profile of two adjacent echoes, the amount of range shift between them can be automatically tracked out. The combined range profile is constructed by a max operation, which only reserves the larger elements of the two echoes, and the echoes’ amplitudes are limited before they are combined. This algorithm has been used to process real ISAR data and the results demonstrate the effectiveness of the method. Compared with the correlation method and the minimum entropy method, the proposed algorithm obtains much better results in both examples in this paper. Its computation complexity has the same order of magnitude as the minimum entropy method.

Improved Classification Approach via GEPSVM

A modified multisurface ＂proximal support vector machine classifier via generalized eigenvalues （GEPSVM for short）＂ was proposed. By defining a new principle, we designed a new classification approach via GEPSVM, namely, maximum or minimum plane distance GEPSVM （MPDGEPSVM）. Unlike GEPSVM, our approach obtains two planes by solving two simple eigenvalue problems, such that it can avoid occurrence of singular problems. Our approach, compared with GEPSVM, has better classification performalce. Moreover, MPDGEPSVM is over one order of magnitude faster than GEPSVM, and almost two orders of magnitude faster than SVM. Computational results on public datasets from UCI database illustrated the efficiency of MPDGEPSVM.

Optimization of line-tapered MMI devices using a genetic algorithm

We discuss the optimal design of line-tapered multimode interference （MMI） devices using a genetic algorithm （GA）. A 1×4 MMI device is designed as a numerical example. Compared with the conventional design based on self-imaging theory, the present method demonstrates superior performance with low in- sertion loss and small non-uniformity.

A Novel Receiver Architecture for DBF Antenna Array

The developments of the high speed analog to digital converters （ADC） and advanced digital signal processors （DSP） make the smart antenna with digital beamforming （DBF） a reality. In conventional M-elements array antenna system, each element has its own receiving channel and ADCs. In this paper, a novel smart antenna receiver with digital beamforming is proposed. The essential idea is to realize the digital beamforming receiver based on bandpass sampling of multiple distinct intermediate frequency （IF） signals. The proposed system reduces receiver hardware from M IF channels and 2M ADCs to one IF channel and one ADC using a heterodyne radio frequency （RF） circuitry and a multiple bandpass sampling digital receiver. In this scheme, the sampling rate of the ADC is much higher than the summation of the M times of the signal bandwidth. The local oscillator produces different local frequency for each RF channel The receiver architecture is presented in detail, and the simulation of bandpass sampling of multiple signals and digital down conversion to baseband is given. The principle analysis and simulation results indicate the effectiveness of the new proposed receiver.

基于塔形形态算法的 SAR图像相干斑抑制(英文)

提出将塔形形态算法用于抑制 SAR图像中相干斑处理 ,为减少塔形处理中由于下采样造成的信息损失 ,从并行处理的角度出发 ,对塔形形态滤波器提出了改进 ,将下采样中的各子图同时进行形态滤波处理 ,在上采样中将各子图合并。经分析和处理表明这两种算法用于 SAR图像滤波都能有效地去除相干斑噪声。与塔形形态滤波、Lee滤波器算法比较 ,采用并行算法处理后图像的各项指标有明显的改善。

A Mo LC+Mo M-based G^0 distribution parameter estimation method with application to synthetic aperture radar target detection

The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar(SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant(Mo LC) + method of moment(Mo M)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new Mo LC+Mo M-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.

位置不确定持续移动对象的离散表示(英文)

基于快照模型 ,提出对多个离散快照进行整体插值来生成不确定性二维移动点对象的离散模型用于时空数据库系统的实现。利用GM (1,1)模型 ,通过灰生成降低各个离散快照本身包含的不确定性 ,建立能够反映移动对象的整体运动趋势的离散实现模型。与线性插值模型的对比实验说明 。