A vegetation parameters inversion algorithm based on Oriented Volume (OV) model is presented for vegetation with polarization characteristics, and the model and the algorithm is verified with a hard-in-loop polarimetric SAR interferometriy system constructed in an anechoic chamber. According to the vegetation characteristics of OV model, the difference of co-polarization represented dihedral scattering mechanism is discriminated as a basis for topographic phase, finally the retrieval vegetation height is gained by calculating the average and standard deviation. Next, a hard-in-loop broadband polarimetric SAR interferometric system is constructed in a controlled environment. The baseline is calibrated by two trihedral angles with height known. The experimental results show that the retrieval height is fluctuated 0.03 m to the actual height, and the inversion error is less than 0.2 m in the whole band, which explain the feasibility of model and the inversion algorithm.

Tetrolet transform, as one of the mutiscale geometric analysis method, can be used to represent natural images sparsely. However, SAR images consist of textures, leading to that the high frequency coefficients of Tetrolet still have large amplitude, and thus affects the sparse representation performance of SAR images seriously. In this paper, a new transform named Tetrolet Packet is proposed. At first, the high frequency coefficients are reordered, and then the high frequency sub-bands are decomposed using multi-Tetrolet transform according to a entropy based cost function. So a optimal Tetrolet tree structure can be found, and the energy of coefficients are concentrated with less direction informations in order to get better performance of SAR image compression. In the experiment, the SAR images are reconstructed with the same number of coefficients of Tetrolet transform and Tetrolet Packet respectively, and their reconstruction performances are compared. The results show that the proposed method Tetrolet Packet outperforms Tetrolet in the sense of sparse representation ability for SAR images, both in visual quality and PSNR. Furthermore, transform coefficients of both methods have similar zero-tree structures, and the compression performance of the proposed method is investigated by employing Modified-SPIHT.

This paper presents a novel classification algorithm of hyperspectral remote sensing image based on sparse representation and spectral information. First, a learning dictionary is obtained based on hyperspectral remote sensing image data set, and then the sparse coefficient of each pixel is calculated according to the learning dictionary. As a result, sparse representation feature is obtained. Finally, random forests are respectively constructed based on sparse representation feature and spectral information, and the classification result is decided by voting strategy. Experiments on AVIRIS hyperspectral remote sensing image justify the effectiveness of the algorithm. The experimental results indicate that the proposed method has better performance than methods based on spectral and sparse representation respectively, and has a higher overall accuracy and Kappa coefficient.

Four-dimensional reconstruction of urban areas and man-made infrastructure is one of the most important applications of differential SAR tomography. In this situation, the urgent problem of differential SAR tomography is how to achieve satisfying elevation-velocity resolution using sparse samples of space-time plane and preserve azimuth-range resolution simultaneously. An imaging method for differential SAR tomography based on RELAXation (RELAX) algorithm is proposed in the framework of deterministic models. Compared the spatial spectral estimation methods with statistical model, this method do not need to implement a spatial multilooking. Compared with the singular value decomposition method, this method has much better resolution. Results obtained by processing simulated data and real data of ENVISAT-ASAR verify the promising potentiality of this method.

In order to solve the contradiction between high-resolution and wide-swath for the spaceborne single- channel SAR system, this paper proposes a new method based on periodic non-uniform sampling. The method uses the non-uniform sampling to avoid the overlap of blind ranges, making the blind from the same range unit appears in one sampling channel mostly; The method uses the periodic sampling to construct the equivalent multi-channel data, and uses the multi-channel unambiguous reconstruction method to reconstruct the signal’s spectrum. The paper also analyzes the optimal design of non-uniform sampling method in detail. Finally, simulation results verify the effectiveness of the method.

A novel method based on anisotropic scale space is proposed to find matches in SAR images, which overcomes the disadvantages of SIFT. First, the anisotropic scale space of the image is constructed using bilateral filters, which removes the speckle while preserving the detailed. Then features are detected and described using SIFT at coarser scales, which reduces the impact of speckles. Finally, matches are found by dual matching strategy, which increases the probability of correct matching. This method increases the number of correct matches while maintaining the accuracy. Through various experiments including slant range images acquired from different times, polarizations, wavelengths and viewpoints, it demonstrates the improvement over SIFT in term of the amount and accuracy of the matches.

Because of its compressed sampling property, Compressive Sensing (CS) has wide application to high resolution imaging. But as a parametric imaging method, CS based imaging methods are sensitive to position error. Position error may cause defocusing, range migration, or even can not imaging. This paper concerns the analysis and compensation of trajectory deviations in airborne spotlight Synthetic Aperture Radar (SAR). A motion compensated CS SAR imaging scheme is proposed based on the sensor measured data. An additional item is introduced into the sparse matrix to achieve the compensation of space invariant motion error. This method can not only get enough information for imaging using few measure position and data, but also reduce the affection of motion error on image quality, achieve high resolution imaging.

This paper employs quaternion theory to angle estimation of collocated bistatic MIMO radar. Quaternion model is constructed from the general data model, and the quaternion Root MUltiple SIgnal Classification (Root-MUSIC) algorithm is proposed for angle estimation in bistatic MIMO radar. This algorithm estimates Direction Of Departure (DOD) and Direction Of Arrival (DOA) via Singular Value Decomposition (SVD) and Root-MUSIC. The angle estimate performance of this algorithm is better than the existing algorithm, and the complexity of the proposed algorithm is reduced very much. The simulation results verify?the effectiveness?of the algorithm.

To relax the heavy requirement of training sample size in the radar High Resolution Range Profile (HRRP) target recognition, a linear dynamic model based recognition method is proposed. Firstly, the statistical characteristic of HRRP’s frequency spectrum is analyzed and considered to be a Wide Sense Stationary (WSS) process. Then a linear dynamic model is employed to model the amplitude of frequency spectrum and an Expectation Maximization (EM) algorithm is adopted to estimate the model parameters. Finally, experimental results based on measured data show that the proposed method can obtain satisfactory recognition accuracy and rejection performance even with a very few training samples.

To solve the problem of target localization in bistatic MIMO radar, a new method based on third-order tensor decomposition is proposed for fast multi-target localization. First, the matched filter output is transformed to a third-order tensor and its dimension is reduced. Then, the transmit and receive steering matrices and Doppler matrix are estimated through Alternate Least Square (ALS) method. Finally, the target Direction Of Departure (DOD), Direction Of Arrival (DOA) and Doppler frequency can be regressed by spectrum estimation algorithms. The Line Search (LS) scheme is used to speed up the convergence of ALS. Compared with the existing approaches, the proposed method avoids two-Dimensional (2-D) spectrum peak searching and covariance matrix estimating, and the target DOD, DOA and Doppler frequency are automatically paired. The estimation performance is improved; meanwhile, the computational cost and storage are effectively reduced. The effectiveness and superiority of the proposed method is demonstrated by simulation results.

A Robust Transmitting Beamforming (RTB) algorithm is proposed for MIMO radar in the presence of unknown transmitted array distortions. The proposed beamformer, which is cascaded with the robust receiving beamformer, is based on the maximization of worst-case Signal-to-Interference-plus-Noise Ratio (SINR). The proposed beamformer belongs to the class of diagonal loading techniques. Numerical experiments show that the proposed beamformer has better robustness, lower computational complexity and faster convergence rate as compared with the other robust beamforming algorithms.

A method based on Singular Value Decomposition (SVD) is presented to solve Tie Points (TPs) detection in Interferometric Synthetic Aperture Radar (InSAR) block. The core concept is to construct a corresponding matrix through SVD of the dissimilar distribution matrix which characterizes the dissimilarity distribution of two descriptors attached to each feature point. The method benefits TPs detection based on combining the corresponding matrix with the ratio of the second greatest value to the greatest one. The algorithm has advantages of high speed, simplicity and technical feasibility. The effectiveness of proposed method is validated by experiments on three adjacent synthetic aperture radar image-pairs of different kinds of terrain.

If another separated receiver is added to a full monostatic high-frequency ground wave radar, a T/R_m-R_b system can be got, one receiver R_m operating in the monostatic mode, co-located with transmitter T, and another receiver R_b operating in bistatic mode. The T/R_m-R_b system for ocean environment remote sensing can not only measure the current vector velocity, but also eliminate the wind direction ambiguity. It is one of the trend in development of high-frequency ground wave radar. In this paper, the distribution principle of T/R_m-R_b system is determined from the optimal baseline length and optimal range of bistatic angle, which are analyzed from the angle of radar detection ability and current measurement error. That is: if the location of T/R_m monostatic radar is known, the optimal baseline length can be firstly determined according to the maximum range sum target of T-R_b bistatic radar, then the optimal range of bistatic angle and the location of the bistatic receiver R_b can be determined according to the minimum current measurement error of T/R_m-R_b system. The distribution principle obtained in this paper will provide useful reference for the application of bistatic (or multi-static) high-frequency ground wave radar to ocean environment remote sensing.

According to the special structure of China Mobile Multimedia Broadcasting (CMMB) signal, this paper presents two methods for reference signal extraction in passive bistatic radar system based on CMMB signal, the adaptive filter algorithm based on the sync signal of CMMB and the method of reference signal reconstruction based on the theory of modulation and demodulation for CMMB signal. The specific processes of the two proposed algorithms are studied first. And next, the performance of the two methods in the typical multipath environment is compared though simulation and real data verifies the effectiveness of the reconstruction method. Analysis demonstrates that signal reconstruction method can eliminate the multipath clutter and interference in the reference signal more effectively, which indicates that this method can extract the reference signal with high purity and the algorithm is more robust.

Available SAR-Ground Moving Target Indication (SAR-GMTI) method based on the forward-looking antenna is mainly Space-Time Adaptive Processing (STAP), which is hard to be practically realized. For this fact, an advanced SAR-GMTI method based on the forward-looking airborne radar is proposed in this paper. This paper establishes the echo model of moving targets, and illustrates the connection between the traditional Displaced Phase Center Antenna (DPCA) systems and this proposed system. The improved DPCA technology is presented for moving target detection, location and velocity measurement. Finally, the simulation results confirm the effectiveness of the improved DPCA technology.

A ground clutter elimination method based on terrain visible analysis is proposed for airborne weather radar that operates in weather mode. Visibility judgment is adopted to identify the range bins containing clutter. The view angles for all sampling points in digital terrain model are computed and its distributing rule is analyzed. The view angles and the depression angle of radar are compared. Those range bins with clutter are edited and rejected, so the suppression is directly implemented. Finally, the validity and effectivity of the method are illustrated by processing the simulation data and the measured airborne data.

Phase synchronization of radar carrier is prerequisite to distributed satellite SAR system. In this paper, a modified phase synchronization means of distributed satellite SAR is proposed, that is, phase synchronization pulses are exchanged between satellites based on the GPS-disciplined crystal oscillators. The factors affecting phase synchronization performance are analyzed, and the performance of phase synchronization link is verified by ground test.

Sub-Nyquist sampling is an effective approach to mitigate the high sampling rate pressure for wideband spectrum sensing. The existing sub-Nyquist sampling method requires excessive large measurement matrix and exact sparsity level in recovery phase. Considering this problem, a method of applying Modulated Wideband Converter (MWC) with small measurement matrix to wideband spectrum sensing is proposed. An improved sufficient condition for spectrum-blind recovery based on the redefinition of spectrum sparse signal model is presented, which breaks the dependence on the maximum width of bands for MWC construction. In recovery phase, the Sparsity Adaptive Matching Pursuit (SAMP) algorithm is introduced to Multiple Measurement Vector (MMV) problem. As a result, a full-blind low rate sampling method requiring neither the maximum width nor the exact number of bands is implemented. The experimental results verify the effectiveness of the proposed method.

Stereoscopic image quality assessment is an effective way to evaluate the performance of stereoscopic video system. However, how to use human visual characteristics effectively is still a research focus in objective stereoscopic image quality. In this paper, combining with the stability characteristics of singular values and subjective visual characteristics of stereoscopic images, an objective stereoscopic image quality assessment model based on Support Vector Regression (SVR) is proposed. In the model, firstly, stereoscopic features are obtained by extracting singular values of left and right images. Secondly, the features are fused according to different types of distortion. Finally, the values of objective assessment are predicted by SVR. Experimental results show that, by applying the proposed model to stereoscopic test database, Person’s correlation coefficient index reaches to 0.93, Ranked correlation coefficient index reaches to 0.94, Root Mean Square Error (RMSE) index approaches to 6, and outlier ratio index reaches to 0.00%, which indicate that the model is fairly good and can predict human visual perception very well.

Local segmentation is the key work in image segmentation. Considering two existing problems, which are the instability of controlling narrow band and the low precision in local segmentation, this paper proposes a new Binary and Selective Morphological Operation Regularized Level Set (BSMORLS) method. Since the traditional signed distance function is replaced by binary level set in the method, and the binary property of the level set is maintained strictly in curve evolution, the stability of narrow band and the precision of one pixel width can be guaranteed. Optional morphological operator is utilized to increase the flexibility of curve smoothing, and sparse field is adopted to reduce the computational complexity. Experiments on some synthetic and medical images indicate the efficiency and robustness of the proposed local segmentation method.

The performance of Direction-Of-Arrival (DOA) estimation of classical algorithms may degrade substantially in the presence of mutual coupling. In this paper, a blind source separation based algorithm is proposed for DOA estimation using uniform linear array. Firstly, the generalized array manifold matrix is estimated using blind source separation techniques; Then, based on the property that the mutual coupling matrix of uniform linear array can be modeled by a symmetric Toeplitz matrix, DOA estimation problem is transformed into multiple separable nonlinear least squares problems, and DOAs can be obtained by multiple one-dimensional peak searching. The proposed algorithm does not need multidimensional peak searching or multidimensional iteration, and imposes weaker constraints on the number of non-zero coefficients in the mutual coupling matrix. Besides, the proposed algorithm is applicable even if the number of non-zero coefficients in the mutual coupling matrix is unknown. Simulation results demonstrate the effectiveness of the proposed algorithm.

For the difficulty or low accuracy on foreground extraction in a complex environment, this paper proposes Bayes-total probability joint estimation for the detection and segmentation of foreground objects and the definition of background error control variable. Under the criterion of Bayes-total probability joint estimation, background pixels will be divided into stationary and moving types by choosing a proper feature vector, and foreground pixels can be detected accurately. Experiment results show the proposed method is a more general model for target detection, and it is also promising in extracting foreground objects under different kinds of background from video (containing complex background).

The landmark-based registration methods do not define an unbiased transformation between the two images, which are not suitable for registering images where there are large deformations. A progressive landmark-based image registration method using Mean Shift is presented. This method is capable of providing unbiased transformations and defining a consistent correspondence between two images. Based on few initial landmark pairs, new corresponding landmark pairs are searched by Mean Shift and tacked in the images gradually to construct unbiased transformations. The progressive registration is conducive to Mean Shift to search corresponding points using satisfied initial position, and avoid Mean Shift dropping into the local minima. Experiments show that the method is simple and feasible to large deformation and small deformation registration problem in the meantime.

The Gaussian Mixture implementation of Probability Hypothesis Density Filter in Linear Gaussian Jump Markov multi-target System model (LGJMS-GMPHDF) is proved to be an effective tool for tracking an unknown and time-varying number of targets with uncertain target dynamics in clutter. This paper further integrates the class information into LGJMS-GMPHDF and proposes a recursive Joint Detection Tracking and Classification (JDTC) algorithm for multiple maneuvering targets in dense clutter. The main idea is to augment the kinematic state vector with the target class vector, and then use their combined measurement likelihood to integrating the target classification information into the update process of LGJMS-GMPHDF. The combined target kinematic state and class measurement likelihood improves the discrimination of different class targets and clutter, so better detection and tracking performance can be expected compared with the original LGJMS- GMPHDF. The classification probabilities and state vectors are updated synchronously. The proposed JDTC algorithm can simultaneously estimate the time-varying number of maneuvering target, their corresponding kinematic states and classes. The algorithm is demonstrated via a simulation example involving tracking of two closely spaced parallel moving targets and two crossing moving targets from different classes, where targets can appear and disappear.

A novel wide-band Direction-Of-Arrival (DOA) estimation method based on space-frequency sparse representation is proposed to estimate the frequency and DOA of narrow band signal with a wide band receiver. The over-complete dictionary is constructed by using space-frequency to replace the 2D combination of frequency and azimuth. Although the length of constructed dictionary equates to the length of narrow signal DOA estimation’s dictionary, it could cover the whole unambiguous frequency. The precise frequency of signal is estimated through frequency spectral searching, and the frequency covariance matrix is constructed based on the position of frequency spectral peak. Then DOA can be obtained using the sparse representation of the large eigenvectors, which are coming form the frequency peak covariance matrix’s Eigenvalue Decomposition (ED). The proposed method has a higher precision in the low Signal to Noise Ratio (SNR), and the number estimated can be much more than the array numbers. The experiment results indicate that the proposed method is correct and effective to estimate the frequency and DOA of narrow signal for wide-band receiver.

This paper proposes a construction scheme of girth-6 quasi-cyclic Low-Density Check-Parity (LDPC) codes based on pseudo-cyclic Maximum Distance Separable (MDS) codes with two information symbols. The parity-check matrix of an quasi-cyclic LDPC code in GF(q) can be constructed by calculating the generator polynomials of pseudo-cyclic MDS code with length q+1 directly. It utilizes mainly the special characteristic of the circularity of pseudo-cyclic MDS codes with two information symbols. Also the distance between arbitrary two codes is not less than q. Therefore, it guarantees no cycles-4 in the construction of the quasi-cyclic LDPC codes. Simulation results show that the quasi-cyclic LDPC codes based on pseudo-cyclic MDS codes perform well in an AGWN channel.

The capacity issue of asymmetric two-way amplify-and-forward relaying is investigated. First, exact and asymptotic outage probabilities of the network scenario under investigation are derived over Rayleigh fading channels. Then, it is found that the system outage probability is determined by the terminals’ average transmission powers and the traffics that the system operates. For most of the traffics, the overall system outage probability depends only on the one-way channel. Following this analysis, novel power allocation and relay location algorithms are proposed, both of which are based on the traffic-knowledge of operating networks. The simulation results show that the outage performance is significantly improved when the proposed algorithms are applied.

The way of controlling transmit power, in a precoding method based on maximal Signal-to- Leakage-plus-Noise Ratio (SLNR) for multiuser MIMO downlinks，is not efficient to ensure each user’s available SLNR value, so a precoding scheme pursuing design goal that minimizes total transmit power under each user’s SLNR constraint is proposed. The goal issues can be successfully solved by using SemiDefinite Relaxation (SDR) techniques, and power constraint condition added in goal issues can efficiently reduce total transmit power of the base station. Simulation results show that the proposed scheme that satisfies large SLNR thresholds, has better Bit Error Rate (BER) and lower total transmit power than the maximal SLNR based precoding method. Moreover, the higher the system Signal-to-Noise Ratio (SNR), the lower the total transmit power of the scheme.

Since preamble-based channel estimation method can overcome the intrinsic inter-symbol interference and inter-carrier interference in OFDM/Offset QAM (OFDM/OQAM) system, it becomes the commonly used structure in similar systems. In this paper, according to the pilot structure and the characteristic of OFDM/ OQAM signal, the correlation between the adjacent sub-carriers is analyzed, and in turn an improved channel estimation algorithm is proposed. Through calculating the correlation coefficient between the adjacent subcarriers, weighting operation is carried out in frequency domain to reduce the effect of interference and noise on channel estimation. Analysis and simulation results demonstrate that this algorithm can effectively improve both channel estimation accuracy and system performances of traditional ones.

H.264 takes objective metric as distortion criteria to perform Rate Control (RC) and Rate Distortion Optimization (RDO)-based mode decision, which can not acquire optimal subjective quality. Base on our previous research results, this paper applies Structural SIMilarity (SSIM) based subjective distortion to RDO-based inter mode decision in H.264 video coding, and further proposes an analytic MacroBlock (MB) layer Lagrange multiplier adjustment scheme to adaptively balance the tradeoff between rate and SSIM distortion better. Experimental results show that, at given target bit rate, the proposed method encodes image structural information more effectively, and thus acquires better subjective RDO performance and image quality compared with objective quality based encoding scheme and SSIM-based RC method (without performing SSIM-based RDO inter prediction).

According to the strong memory effect characteristics of the broadband RF power amplifier, this paper presents a new predistortion method, and it is termed as Parallel MP-EMP-CIMT (PMEC). The new predistorter is constructed of three parts, Memory Polynomial (MP), Envelope Memory Polynomial (EMP) and Cross Items between Memory Times (CIMT). Compared with the traditional Hybrid MP-EMP (HME) method, PMEC method increases the cross items between different memory times, in order to solve the problem of high system complexity, the EMP predistorter is simplified and the high order nonlinear terms of CIMT predistorter are cut off. The measure results show that PMEC method can acquire better linear effect than the MP method and the HME method. Compared with the MP method, PMEC method reduces the third-order ACPR of output signal by 1.07 dB/1.32 dB, and cut down 18.75% of the predistortion coefficient; Compared with the HME method, PMEC method reduces the third-order ACPR of output signal by 0.2 dB/0.99 dB, using 79.59% of the predistortion coefficients.

In order to improve the computing efficiency of k₁P+k₂Q in elliptic curve cryptosystem, a new seven- element Joint Sparse Form (JSF) is proposed in this paper. For any pair of integers, the definition and calculating algorithm of the new seven-element JSF are given, and the uniqueness of the new seven-element JSF is proven. Besides, it is also proven that the average joint Hamming density of the new seven-element JSF is 0.3023. When computing k₁P+k₂Q, the new seven-element JSF reduces 0.1977l point additions comparing with the optimal three-element JSF, and reduces 0.031l point additions comparing with an existing five-element JSF, and reduces 0.0392l point additions comparing with another existing seven-element JSF.

Available Attribute-Based Authenticated Key Exchange (ABAKE) protocols are all designed in the single Attribute Authority (AA) environment. However, secure communication is in demand between parties from different Attribute Authorities (AAs). Based on Waters’ attribute-based encryption scheme, an ABAKE protocol is proposed in multiple AAs environment and the security of the proposed protocol is reduced to Gap Bilinear Diffie-Hellman (GBDH) and Computational Diffie-Hellman (CDH) assumptions in the Attribute-Based extended Canetti-Krawczyk (ABeCK) model. Moreover, the scheme, which transmits attribute authentication policy represented by linear secret sharing scheme via Boolean formulas, can express flexible policies and decrease communication cost drastically.

Using dual system encryption, a attribute-based encryption scheme with hidden access structures is proposed in prime order bilinear group in this paper. The scheme relies on the D-Linear and Decision Bilinear Diffie-Hellman (DBDH) assumptions, and is proven fully secure under standard model. Moreover, it is suitable for the system with lower storage devices and higher efficiency computations because it achieves constant size private key and constant length of pairing computations.

Using Learning With Errors (LWE) in the lattice, the equation test is converted to a decryption ability of a random string. It solves the secure two-party computation such as the relationship of an element and a set, set intersection, and set equation etc. The simulations in the semi-honest model show that these two-party solutions are secure and efficient. Compared with protocols based on security assumptions in number theory, the proposed protocols not only have lower computational complexity without exponential operations but can also resist quantum attack because of the assumption on lattice problem.

To construct Reconfigurable Service Carrying Network (RSCN) in Reconfigurable Flexible Network (ReFlexNet) infrastructure can effectively solve the puzzle faced by traditional internet infrastructure. Resilient construction problems of RSCN in the precondition of physical link prone to failure are discussed. Mathematics model of RSCN resilient construction issues are established. To avoid enormous influence because of important resource failure, a Resource Stress Factor (RSF) Awareness RSCN Construction Algorithm named RSF-ACA is proposed. To improve success running ratio of RSCN, RSCN Link Failure Recovery Algorithm named RSLFRA is implemented when single link failure takes place. The efficiency of algorithms is evaluated by emulation experiments according to RSCN success running ratio and different RSF resource distribution and physical link utilization under several scenarios.

A real-time system is required to guarantee its stringent requirements in real-time response and reliability since any task’s failure to response correctly within its deadline may result in a catastrophe. Based on the rollback recovery fault-tolerant model, a fault-tolerant priority decrease strategy is proposed, which allows the faulty task to execute at lower priority levels, to improve system fault resilience. Then, the schedulability analysis is presented based on the derivation of computing formula of task’s worst-case response time under the new strategy. To find out an optimal fault-tolerant priority decrease assignment quickly, an efficient priority assignment search algorithm is proposed, which reduces the search space from O(n!) to O(n²). Finally, the simulation shows that the new strategy can improve system fault resilience efficiently.

Reflector antenna with defocused array feed is investigated. The phased array feed moves towards the reflector and locates at the defocused area, which can enhance the beam reconfiguring ability and limited angle scanning capability. Improved projection matrix algorithm is adopted to get the excitation coefficients of the feeding phased array under phase-only control constraint. A numerical analysis is carried out in order to demonstrate the effectiveness of the approach. The patterns of the offset parabolic antenna fed by defocused feed array are effectively synthesized, including scanning and reconfigurable beams. The beam direction, beam-shape and side-lobe level requirements are met under phase-only control. The design results are verified by the simulation software GRASP.

In the Triple Module Redundancy (TMR) design for the FPGA, the feedback loop of the register will lead to the persistent errors which would have a negative impact on the fault-tolerant capability of the triple module redundancy design, hence the voter insertion in the feedback loop is necessary. This paper presents a triple module redundancy design method to the mapped netlist for the first time, and proposes a voter insertion algorithm based on the critical path. This algorithm proposed can avoid inserting the voter in the critical path and alleviate the negative impact on timing performance during voter insertion. Compared with the similar algorithms, the proposed algorithm can reduce the critical-path delay by 3% to 10% and improve the run time averagely by 35.4% while keeping the design reliability non-decreasing with less than 1% area penalty.

For the problem of great series motional resistance in Micromechanical (or MEMS) disk resonator, a novel moving-electrode approach is presented to reduce the electrode-disk gap and the series motional resistance of resonator. This approach introduces the tunable property of other RF MEMS devices to disk resonators in the existing fabrication conditions. The series motional resistance of the disk resonator is reduced. The paper introduces the theory and design of the disk resonator with suspended electrode, derives the effective gap width after electrode’s moving, proposes a circle-shaped groove produced by hole in a mask to solve the point contact problem between electrode and disk and analyzes the effect of circle-shaped groove on the effective gap width. In ANSYS10.0, the suspended electrode is pulled in the fixed bar with voltage of 2.10 V (0.1 μm) or 66.38 V (1 μm) and gap of 0.0016 μm or 0.01 μm. For 0.1~1.1 μm gap resonator, the series motional resistance drops below its 10^-8 times.

Spectral endmember extraction is an important pretreatment for the further analysis of hyperspectral data. Regarding many kinds of endmember extraction algorithms, N-FINDR algorithm is widely utilized for its full-automation and better endmember extraction performance. However, the order of the samples has a certain effect on the endmember extraction, and traditional N-FINDR algorithm also needs to reduce the dimensionality based on the number of the endmembers, which will limit its application. In the actual hyperspectral data, the incompact clustering of the same species presented in the high dimensional space also increases the difficulty of endmember extraction. So this paper proposed an improved stop rule and the pretreatment of the features, and utilizing Support Vector Machine (SVM) to conduct the second endmember extraction. Experiments show that the improved stop rule further increased the volume of the convex polyhedron composed of the endmembers. The pretreatment of the features and the second SVM endmember extraction increase the separability of the data and the precision of the extracted endmembers respectively.

Precision analysis of the bistatic spectrum is the precondition of designing imaging algorithms. For the constant-offset case, the precision analysis of the spectrum is given in detail in the frequency domain. The spectrum is exactly analytical when the restrictions of the bistatic angle and the baseline to range ratio are both met. Neither the baseline to range ratio nor the squint angle is a constraint explicitly. Experimental results validate the accuracy of the discussion about the restrictions of the spectrum.