Information sharing and baseline measurement inter-satellites are key technologies for the space based virtual exploring mission of Distributed Spacecraft(DS). The integrated mode of inter-satellite communication and baseline measurement for DS is proposed, the method of precisely ranging and time synchronization by bidirectional Asynchronous transfer frame via inter-satellite direct sequence spread spectrum link are researched, then the iteration algorithm of asynchronous ranging/time synchronization and model error of the algorithm is proposed and analyzed. The experiment results and analysis of experimenting system show that the integrated mode of inter-satellite communication and baseline measurement presented in the paper achieves excellent precision, functions integrated in one device with more effective utilization of radio channel, and provides a advantage design approach for the space mission of DS.

A serial Turbo-DFH iterative demodulation and decoding scheme is proposed, with regarding the frequency transition as some code. In the scheme, the encoder consists of an outer encoder and an interweaver, serially concatenating with a transition function. At the decoder, a serial iterative structure is adopted to decode the codes. A novel soft-input and soft-output algorithm for DFH system is deduced. The simulated result shows that compared with the traditional DFH demodulation algorithm, the performance is improved obviously.

A cross-layer packet scheduling algorithm is proposed for multi-user MIMO-OFDMA systems with the mixed services, such as Real-Time (RT) and Non-Real-Time (NRT) services. The proposed scheduling algorithm is based on the channel state information of physical layer and user queuing delay of Medium Access Control (MAC) sub-layer, and constructs the corresponding utility functions for different types of services. Simulation results show that this algorithm can not only guarantee the delay requirements of RT service but also obtain good system throughput and satisfy the fairness criterion.

This paper investigates adaptive resource allocation scheme to maximize the sum-rate under the QoS constraint for multiuser MIMO/OFDM downlink. Specifically, the basestation exploits spatial division multiple access (SDMA) to support several users in each subcarrier, and linear precoding to reduce inferences among users. An adaptive power and bit allocation scheme with guaranteed QoS is provided. And two low-complexity suboptimal bit fill and bit removal algorithms which could be used in practical systems are proposed. Simulation results show that these two algorithms achieve nearly the same performance as the optimal one.

Call admission control (CAC) is one of the most important parts of resource management in mobile communication systems. It keeps the system work stable by accepting or rejecting users’ service requests. CAC solves the conflict between the service satisfaction of user and system resource utilization. This paper focuses on the dynamic CAC strategy providing guaranteed fairness in the CDMA systems with non-uniform traffic distribution among cells. A novel CAC strategy, which can support multi-traffic with different QoS requirements and VBR traffic, is proposed based on former research achievements. By adopting greedy algorithm, whether accepting or rejecting a new call request depends on the target Signal-to-Interference of the whole system. Therefore the equilibrium of blocking probability among cells with different arriving rates and the access fairness is guaranteed. It is very significant for practical system applications.

In this paper, a novel dynamic spectrum sharing scheme combining Spectrum Adaptation (SA) and MIMO-OFDM is proposed. In the scheme, an improved model due to signal power thresholds is adopted to accomplish spectrum adaptation for unlicensed users. In order to achieve the rate maximization, a dynamic power allocation algorithm is also presented. Simulation results indicate that the propositional scheme solves the partial interference problem of Interference Temperature Model (ITM) and the system performance is further improved via using MIMO technique. The proposed algorithm reduces the computational complexity and improves the spectrum efficiency.

The frequency offsets and channel gains estimation problem for MIMO system in the case of flat-fading channels is addressed. Based on the MUSIC (Multiple Signal Classification) and the ML (Maximum Likelihood) methods, a new joint estimation algorithm of frequency offsets and channel gains is proposed. The new algorithm has three steps. A subset of frequency offsets is first estimated with the MUSIC algorithm. Then all frequency offsets in the subset are identified with the ML method. Finally channel gains are estimated with the ML estimator. The algorithm is a one-dimensional search scheme and therefore greatly decreases the complexity of the joint ML estimation, which is essentially a multi-dimensional search scheme.

A novel two-user cooperative diversity scheme based on concatenated channel code and distributed space-time block code is proposed in this paper, and the close form expression and numerical results of channel capacity, outage probability and bit error rate for the quasi-static rayleigh fading channels are also presented by theoretical derivation and system simulation. Through integrating with channel coding and space-time coding, system capacity has been greatly enlarged, and the outage probability is distinctly reduced also. The performance analysis and simulation for the transmitted scheme, which is based on concatenated convolution code and distributed space-time block code under the interuser channel is noisy, is carried out exhaustively. Numerical results show that, even though the interuser channel is noisy, the proposed scheme in this paper is better than traditional cooperative diversity in every respect, such as the channel capacity raised obviously, outage probability and bit error rate decreased greatly.

In this paper, a multilevel coded ultra wideband system with combined iterative pulses demapping and decoding algorithm is proposed. The simulation result of three level coded ultra wideband systems show that the bit error performance has been improved prominently compared with uncoded situation. Iterative multistage algorithm and iterative parallel algorithm can achieve optimal performance through three and four iterations respectively in AWGN channel, but in indoor multipath channels, two and three iterations are enough to get the optimal performance respectively. Compared to iterative multistage algorithm, iterative parallel algorithm achieves equivalent performance under optimal iteration and requires only about 1/3 time delay than latter.

Based on the immune clonal selection theory and the novel genetic quantum algorithm, an Immune Clonal Quantum Algorithm (ICQA) is proposed to solve high complexity of optimum multiuser detection in code division multiple access systems. Using this algorithm, the vaccine based on Hopfield neural network is inoculated into the Clonal Quantum Algorithm (CQA ) to improve further the fitness of the population at each generation. Such a hybridization of the CQA with the stochastic Hopfield neural network reduces its computational complexity by providing faster convergence. In addition, a better initial data estimation supplied by the CQA improves the performance of the vaccine, and the inoculated vaccine improves the performance of the CQA. The uniform theoretic framework of the making vaccine based on the stochastic Hopfield neural network is presented. Simulation results show that the proposed detector not only can achieves the global optimization value in fast convergence rate, but also is obviously superior to the conventional detector and the multiuser detectors based on previous intelligent algorithms in cancellation of the multiple access interference and the near-far effect.

A modulation classification method for phase-amplitude-modulated signals transmitted through frequency-nonselective fading Multi-Input Multi-Output (MIMO) channels is presented based on Sequential Monte Carlo (SMC) method. An equivalent dynamic state space model is first derived from the MIMO channel. Then the probabilities of all possible modulation types of different transmit antennas can be calculated by sequential importance sampling and type-move step. Finally, noise average is realized utilizing the un-correlation of transmitted data symbols over N channel observation lengths. Moreover, modulations classification is achieved along with estimation of transmitted data symbols. The complexity of the proposed method is linear with the observation channel lengths, number of transmit antennas, sample size, and cardinality of modulation constellation. Simulations show that the proposed method performs well on various constellations.

An Unscented Kalman Filter (UKF) based noncoherent detection method for Chaos-Shift-Keying (CSK) communication system is proposed in this paper. The first symbol is used as the training symbol. The carrier signal is estimated from the received signal over the interval of the first symbol duration by using the unscented Kalman filtering algorithm. Then the estimated carrier signal is multiplied with the successive received signal, respectively, to demodulate the successive transmitted symbols. In comparison with the coherent detection method, this algorithm does not require chaos synchronization. In comparison with the existing noncoherent detection methods, simulation results indicate that the method has better BER performance, even outperforms that of the FM-DCSK communication system.

In this paper, an optimal adaptive multiuser subcarrier allocation with partial-channel response is proposed. This algorithm reduces computational complexity without apparent performance attenuation based on multiusers’ feedback information and dynamic subcarrier allocation method by considering partial-channel response caused by delayed feedback information or estimate error. Simulation results show that the proposed method decreases the impact of partial-channel response and computational complexity obviously with gaining an approximative performance compared with traditional subcarrier allocation method at the same time.

Compared with the conventional Time-Division Multiplexed (TDM) channel estimation scheme based on training sequences, the use of implicit training saves valuable bandwidth, where the training sequences are added to information sequences before antenna transmission. However, for a fixed total transmission power, the information power decrease with the increase of the training sequence power, which causes decrease in the Signal to Noise Ratio (SNR) at channel equalizer. In this paper, the relationship between the SNR of the channel equalizer and the training sequences power is analyzed for MIMO system. The optimal power allocation of the training sequence is derived based on the criterion of maximizing SNR of the equalizer. Analysis and simulation results show that the SNR of the channel equalizer is maximized at the optimal training sequence power, and the optimal power of the training sequences is increased with increase of the signal to noise ratio at the received antennas.

A new combined MSDD iterative differential demodulation and channel decoding algorithm based on Soft-Input Hard-Output(SIHO) Viterbi decoding algorithm is presented. The new algorithm includes feed-forward iteration method and feed-backward iteration method. Numerous simulation results show that the proposed feed-backward iteration method can get performance only worsen than QPSK corherent demodulation is 1.1dB. Test results of satellite communication demodulator based on FPGA show that the performance only worsen than simulation results about 0.5dB.

Theoretical models of envelope making and phase making of optical fiber chaotic secure communication are studied by coupling the chaotic encoding multiple-quantum-well laser systems and an optical fiber channel. Effects of the self-phase modulation of optical fiber and optical amplifier number are analyzed. The modulation and demodulation quality is analyzed and an encoding formula is demonstrated. A phase controller can be used to reduce the effect of nonlinear phase shift of fiber on the synchronization and demodulation. Finally, envelope making with a bit rate of 0.2Gbit/s and phase masking with a bit rate of 0.05Gbit/s are simulated in long-haul optical fiber secure communications at wavelength 1.55μm. The systems have good secure performances.

SIP is used in IMS to perform multimedia session setup and maintenance. However, it is text-based and has large messages with sizes frequently exceeding several hundred bytes during the session setup. As a result, it causes more call setup delay. Based on the SigComp, a new algorithm with improved LZW and HUFFMAN is proposed in this paper, which is named as LZW-HUFFMAN. Simulation results prove that the new algorithm can effectively reduce the message sizes and shorten the session setup delay.

A Cooperative Network Coding technique based on Space-Time code (ST-CNC) is proposed, which combats channel fading and improves resource efficiency and network throughput. A close form expression for theoretical Bit Error Rate (BER) performance of the information exchange in two-hop chain network is derived and its diversity gain and network coding gain is analyzed. The numerical results show that the BER performance of ST-CNC outperforms the traditional strategies with distinctive gains. Furthermore, the simulation results coincide with the theoretical results well.

An Impulse Radio UWB (IR-UWB) system uses very narrow pulses with time-hopping and time diversity to transmit data, where the signals have very low duty cycle. In this paper the cause of data frame transmission failure is analyzed in a distributed IR-UWB network using the ALOHA protocol, and the failure probability is derived. Based on queuing analysis of the data frame generating-buffering-sending process, the network throughput and frame transmission delay in closed-form expressions are obtained. Simulation results show that the throughput, frame transmission delay and stability of the ALOHA IR-UWB network is much better than those of the ALOHA network based on carrier modulation technology.

An extension MAC Protocol based on 802.11e is proposed for better supporting Class of Service in data link layer of Ad hoc. By using multiple reserving channel method, the superiority of the higher priority flows in medium contention is enhanced. By using the diffusion of innovation theory, the low priority flows lower their sending probability to protect the higher priority services, and information flooding is avoided in the whole ad hoc network. Analysis and simulation results show that the extension protocol can improve the success of the high priority data’s throughputs and remarkably reduce end-to-end delay and jitter.

A new Markov chain model for the IEEE 802.11e EDCA is presented. The model takes into account both the idle state and differentiation based on different AIFS-value for different traffic. The signal transfer function of the generalized state transition diagram can be used to derive a probability distribution of the MAC layer service time and the performance of EDCA from a non-saturated channel to a saturated medium by using presented M/G/1/K queuing model is analyzed. A good match between the analytical model and simulation which conforms the veracity of proposed model is observed. Simulation shows that despite providing prioritized QoS, the EDCA still can not support strict QoS for real-time application. It is inevitable that there is unfairness of channel access to prioritized traffic due to EDCA.

The existing mobility support scheme in Host Identity Protocol (HIP) does not support micro-mobility. In this paper, a new mobility support scheme in HIP based on dynamic hierarchical location management is proposed. The Internet is separated into some autonomous areas while each autonomous area is separated into some registration areas. When the node moves in the same registration area, it updates its registration at Local RendezVous Server (LRVS). When the node moves in the same autonomous area, it updates its registration at Gateway RendezVous Server (GRVS). The node selects LRVS and determines the optimal size of registration area according to its mobility and packet arrival rate. Analytical results show that the new scheme outperforms the existed mobility support scheme in terms of reducing the overall signaling cost.

In this paper, based on studying the routing algorithm and re-router model of MPLS Traffic Engineering，a new routing model S-DQRA is proposed. It not only considers the practical requirements of the traffic when the LSP is initially established, but also guarantees reasonable resource utilization. Moreover, for the warrant of more reliable service, a novel re-router model S-DQRRA is proposed based on the S-DQRA model. It works when any invalidation occurs, and switches the traffic from the work path to the backup path. Finally, extensive simulation using NS-2 is conducted to verify the effectiveness of these two models. Compared with the classical models, the experimental results indicate that the models have the favorable working performance.

In order to solve the two major drawbacks of Baptista’s chaotic cryptosystem and its modified versions——excessive length of ciphertext and unbalance ratio of bit 0 to bit 1, this paper gives the lower bound of the expectation of the cipher N-to-plaintext ratio by calculating the entropy of the ciphertext. Then exploiting truncated equal length coding, the optimal truncated equal length coding and so on, this paper describes the relationship between coding and cipher N-to-plaintext ratio, and proposes the approximate formula to work out the ratio of bit 0 to bit 1. Numerical paradigms show that the optimal truncated equal length coding can efficiently shorten the length of ciphertext and obtain more uniform ratio of bit 0 to bit 1.

Based on the structure of quasi-cyclic LDPC codes, a synchro partially parallel decoder is proposed in this paper. In the decoder, the check node process units and variable node process units work concurrently, where the new generated soft information is used in advance during the iteration process to accelerate the convergence speed. Furthermore, differential evolution is utilized to optimize the start positions of node process units in order to achieve better performance. Simulation results show that the proposed scheme outperforms others both in performance and complexity, and is very suitable for the implementation of high speed decoders.

A Low Density Parity Check (LDPC) coded Adaptive Modulation and Coding- Orthogonal Frequency Division Multiplexing (AMC-OFDM) system is proposed, and its theory is given in detail. In order to solve the problem that the traditional Modulation and Coding Scheme (MCS) selecting rule improves the performance limitedly, two MCS selecting rules are proposed for the AMC system, in which MCS for an adaptive block is determined by the posteriori Signal-to-Noise-Ratio (SNR) of units in the block. Throughput performance is analyzed for the two rules. Simulation results show that they can bring to much higher throughput than the traditional method when applied in LDPC coded AMC-OFDM system.

The key to improving the performance of QC LDPC codes is how to construct a parity-check matrix H with a girth distribution as good as possible. In this paper, a novel algorithm for constructing QC LDPC codes, GirthOpt-DE algorithm, is proposed, which achieves a good girth distribution based on the differential evolution. Simulation results show that the performance of the QC LDPC codes constructed with the proposed algorithm is superior to Array codes and Tanner codes in both BER and the minimum distance. Besides, the proposed algorithm is more flexible for designing the QC LDPC codes with desired block length and rate as well as good girth.

A class Double Repeat Accumulate (DRA) codes is provided without small cycles by the jointly design among repeater, combiner and interleaver in this paper. Degree distribution is optimized based on EXtrinsic Information Transfer (EXIT) chart. Simulation results show that this class DRA codes has more flexible degree distributions and lower error floor when belief propagation algorithms is used.

Unequal error protection code is used widely in picture and video transmission. Traditional Turbo Product codes do not have unequal error protection. This paper gives a way to produce unequal error protection Turbo Product codes, and the performance simulation verify its correction.

In this paper, soft semi-definite relaxation for detection of 16-QAM signaling in MIMO systems is investigated. Additional constraints and dimension-reduction approximation method are proposed, which can be used to calculate the Log-Likelihood Ratio (LLR) and reduce dimensions of the SDR detection, respectively. Simulations show that the soft SDR detector exhibits a better performance in a flat-fading MIMO channels, and the complexity of the soft detector is considerably reduced by reducing the dimensions of the SDR programming, but the performance loss leads by dimension reduction is about 0.2 to 0.4 dB.

There is mutual contradiction between direction estimation of user’s signal and power allocation among all users in the beamforming algorithm. A twice game beamforming algorithm based on game theory is proposed to deal with it. Beamforming game algorithm mathematics model is constructed. During the first game, direction of signal and power allocation are mapped the game theory as “player”, which are modeled as the problem of maximin function and obtain direction estimation first. Then during the second game, power allocations of different users are described as a multi-user game. Power updated algorithm is designed. The existence and uniqueness of the Nash equilibrium in the twice game beamforming algorithm based on game theory are proved by mathematics derivation. Finally in simulation the proposed algorithm is compared with conventional maximum SNR algorithm. The results show that the proposed algorithm is better than MaxSNR algorithm and the impact of different parameters on the proposed algorithm is discussed.

HMM model is a double random processing which is trained with B-W algorithm, this algorithm based on hill-climbing is easy to lead to locally optimal solutions and its validity is greatly depend on model initial parameters. In order to improve the validity of model, this paper proposes a hybrid training method which combine the B-W algorithm with improved SA algorithm. With this hybrid method the validity of model is not influenced by the model initial parameters and the global optimal solution can be easily gained. Applying this hybrid method to check transmitter power, the experimental results show that proposed method is practical method and own qualities such as high veracity, rapid converged and good stability.

A novel joint 2-D angle and noncircularity phase estimation for noncircular signals using dual parallel linear subarrays called extended NC-MUSIC (EN-MUSIC) algorithm is presented. The azimuth, the elevation and the noncircularity phases estimated by EN-MUSIC are paired automatically. The resolvable number of sources for EN-MUSIC can be larger than the number of sensors of each subarray. The estimation precision of 2-D angles by EN-MUSIC algorithm is approximately equal to two dimensional unitary ESPRIT for noncircular signals (2D-NC-UESPRIT), and is better than the DOA Matrix (DOAM) algorithm.

A binary wavelet transform-based embedded lossless image coding algorithm called Progressive Partitioning Binary Wavelet-tree Coder (PPBWC) is proposed. In the PPBWC, by using a hybrid coefficient scanning technique, symbols are yielded through the sorting of wavelet coefficients according to the absolute values. The symbols are then encoded using a non-causal adaptive context modeling which takes the advantage of self-similarity between coefficients at different subbands and employs the future information of the encoding coefficient to improve the compression efficiency. Hybrid coefficient scanning and non-causal adaptive context modeling are the major factors that contribute to the compression gain of the PPBWC. Experimental results show that the PPBWC outperforms most of other embedded coders in terms of coding efficiency.

The tap-length and tap-weight adjusting problems of adaptive filter are converted into a single tap-weight adjusting problem. Based on this, a general tap-length updating formula and a new variable tap-length LMS algorithm are presented. The rationality and convergence property of the new algorithm are analyzed. The new algorithm uses time-mean square error to estimate steady state mean square error of the long and short filter and employs adaptive tap-length step size, thus it can update the tap-length fast before the tap-weight converges. It is also proved that several existing variable tap-length algorithms in the literatures can be regarded as special cases of the general updating formula. The theory analysis and numerical simulation results verify the new algorithm.

The a priori Signal-to-Noise Ratio (SNR) is the dominant parameter in noise reduction techniques. This paper analyses several typical estimate approaches of the a priori SNR firstly, and then expresses them in the same form, finally presents an improved estimate of the a priori SNR, which is based on the united speech presence probabilities. Simulation results verify that the performance of the proposed estimator is better than those conventional estimators in terms of the segmental SNR and the log-spectral distance.

In the state space method based speaker tracking system, the nonlinearity of the measurement function degrades the localizing accuracy of the speaker tracking method severely. The iterated central difference Kalman filter algorithm, which incorporates the iterated filtering theory and the Central Difference Kalman Filter (CDKF) method, is proposed to reduce linearization error. In comparison with traditional CDKF method, the proposed method has higher tracking accuracy, faster convergence speed and more robust stability. Simulation results demonstrate the effectiveness of the proposed method.

This paper describes an unsupervised translation disambiguation method based on the Equivalent Pseudo Translation (EPT). EPT is constructed by using non-ambiguous words of target language, which is semantically equivalent to the source ambiguous words. Sense-tagged examples are automatically extracted from a large scale Chinese corpus, by which a semantic classifier of EPT is formed. In order to apply the EPT classifier, English examples are mapped into a set of Chinese words by Hownet. This method is evaluated on the Senseval-2 framework of English lexical sample task, achieving the top performance against all other previous works which extract sense-tagged examples automatically. The results are very close to the state-of-the-art comparable unsupervised systems.

A novel information hiding algorithm for VQ compressed images is presented. Labeling the codewords by the nearest selecting method and using the presented algorithm, secret data can be embedded in the codewords’ indexes of VQ coded image. The method is simulated in computer and better experimental results are given.

Infrared images always have little priori-information and blurry boundaries or even with discontinuous boundaries, and therefore the segmentation of infrared image is very difficult. A variational formulation level set model based on the image global information is obtained, which can detect contours both with and without gradient based on global information and eliminate the re-initialization procedure. The stopping term does not depend on the boundary gradient of the image, which overcomes greatly the “over segmentation”. This algorithm forces the level set function to be close to a signed distance function, and therefore reduces the number of iterations and the error of re-initialization. The method is used in the segmentation of an infrared image, and the experiment results reveal the effectiveness of the algorithm listed in this paper.

A novel feature extraction algorithm is presented for the recognition of traffic sign symbols undergoing degradations in this paper. In order to cope with the degradations, the Combined Blur-Affine Invariants (CBAIs) are adopted to extract the features of traffic sign symbols without any restorations which usually need a great amount of computations. A new magnitude normalization method is proposed for the great differences of magnitude of combined blur-affine invariants. Under the deep discussion of PNN and K-means algorithm, a probabilistic neural network classifier is designed using global K-means algorithm and applied to the classification of degraded traffic signs. The simulation results indicate that CBAIs are efficient for the feature extraction of degraded images, and the designed network is not only parsimonious but also has better generalization performance.

Linear Discriminant Analysis(LDA) is one of the most popular linear projection techniques for feature extraction. The major drawback of applying LDA is that it often encounters the Small Sample Size(SSS) problem. Besides, their optimization criteria is not directly related to the classification accuracy. In this paper, an improved null space LDA method based on DCT is proposed to solve both problems. First, by employing the DCT instead of the “pixel grouping” and redefining the within class scatter matrix, a new null space method is given. Then, combining this method with F-LDA an efficient new feature extraction algrithm is proposed for face recognition. Experimental results show that this method achieves better performance than existing ones.

Most of traditional clustering algorithms get a partition of sample set with mutually exclusive classes, while there is no explicit boundary between classes mostly in the real world. Introducing rough set theory into clustering analysis, this paper proposes a kind of overlapping-based rough clustering algorithm called KMMRSC which represents a class with multiple centroids and describes the belongingness of samples with the concepts of upper approximation and lower approximation, thus there is overlapping relationship between classes. Experiments show that the algorithm KMMRSC, which can find non-spherical clusters, outperforms classic k-means.

An squint mode image formation algorithm for “Tandem” Bistatic Synthetic Aperture Radar(BSAR) is addressed in terms of its geometry and echo models, which is relative to second range compression in monostatic SAR. Aspects of second range compression, range migration and azimuth focusing, which are different with those in monostatic SAR due to the separation of receive-transmit platforms, are resolved successfully. The algorithm is validated for bistatic SAR with arbitrary bistatic angle geometry.

Feature extraction based on PCA for 2 dimensional images has the disadvantages of evaluating the covariance matrix accurately with great difficulty and high computational complexity, 2-dimensional PCA (2DPCA) overcomes these flaws. However, a drawback of 2DPCA is that it needs more features, since it only eliminates the correlations between rows. In this paper, two-stage 2DPCA is applied to further compress the dimensions of features and decrease the recognition computation. Experimental results performing on SAR ground targets based the Moving and Stationary Target Acquisition and Recognition (MSTAR) database indicate that two-stage 2DPCA combining with the pre-processing method in this paper not only decreases sharply feature dimensions, but increases recognition rate, and is robust to the variation of target azimuth.

This paper presents an algorithm about SAR image change detection based on Principal Component Analysis(PCA). This method reshapes the SAR images matrix into vectors, and analyzes the matrix which is composed of the two vectors with PCA process, getting a conclusion that the minor component image is the change portion. This paper also realizes high-effectively the algorithm for SAR image change detection . Finally, compared with the methods based on the Log-Ratio and Multi-Block PCA, it is proved to be valid and effective.

“Layover” is a nodus in SAR imaging. The unitary ESPRIT algorithm was introduced to resolve the layover problem on the frame of multibaseline InSAR in this paper. The data model of multibaseline InSAR with layover was expatiated firstly, and the layover problem in multibaseline InSAR was boiled down to the estimation of the interferometric phase angle. The basic principle and advantage of the unitary ESPRIT algorithm was depicted, its efficiency was validated by the Monte Carlo simulations. The simulations indicate that unitary ESPRIT algorithm can work well when the looks are very small but the performance of other algorithms degrade sharply.

A new method based on cyclic-correlation character for estimating the Doppler and multipath time delay of the wideband echoes for LFM pulse radar by only one pulse signal is presented. First, the Doppler is estimated by energy cumulation of multipath component based on cyclic-correlation transform. Then, an order-reduced signal is reconstructed combining the Doppler with the prior knowledge of the transmitted signal, and the echoes signal is converted to many single-frequency signals. Finally, the multipath time delay is obtained by zero-frequency section cyclic-spectrum where the overlapping echoes can be separated and the resolution is doubled. The method is adapted for low SNR noise, can restrain the affection of the cross-items, and has a high time-delay estimation resolution. Some computer simulations are given in this paper and the results show that the new method is valid.

In order to solve the problem of model mismatch when using parametric approach to estimate the density of High-Resolution Range Profile(HRRP) in radar target recognition, a nonparametric method—Stochastic Learning of the Cumulative(SLC) is presented for the density estimation of HRRP. SLC uses a multiplayer network to estimate the distribution function of the training samples and obtains density by taking derivative. SLC not only describes the density function more comprehensive and accurately, but also avoids the problem of being sensitive to window width that many nonparametric approaches may suffer. Experimental results using outfield real data demonstrate the validity of the proposed learning algorithm.

Polarimetric Interferometric SAR (PolInSAR) is a new advanced technique recently based on measurement techniques of polarimetric SAR and interferometric SAR, and making use of PolInSAR data for retrieving the vertical structure parameters of the vegetation layer becomes the hot research topic of the PolInSAR at present. The most useful Single-baseline PolInSAR inversion algorithm is the three-stage inversion algorithm, which was proposed by Cloude and Papathanassiou, but this algorithm has the errors on the its three aspects: coherence estimation, line fitting and volume coherence estimation, and this errors straightly effect the inversion precision. This paper proposes a new inversion algorithm based on the statistic characteristic and PolInSAR phase optimization algorithm, and takes the PolInSAR simulated data to prove the validity of this algorithm.

When an airborne platform on which Synthetic Aperture Radar (SAR) mounted on flies very complicatedly over subaperture time, traditional quadratic phase error can not depict the errors introduced by the platform motions, and the phase errors need be modeled as polynomial errors with higher order. A new algorithm to extract polynomial errors with higher order from SAR echoes, named as Time Phase Adjustment by Contrast Enhancement (TPACE), is proposed in this paper. The TPACE takes the contrast function as object function and the polynomial coefficients of phase errors as variables to be estimated, directly extracting those coefficients by optimization. The gradient of the contrast function with respect to the variables, which is the key point to implement TPACE algorithm, is derived detailed in the paper. Compared to those existed algorithms that can extract polynomial phase errors, the computation load of TPACE is much less and the TPACE is very useful for real time processing. The results processing real ultra-wide band SAR echoes show the method can extract effectively polynomial phase errors from SAR echoes.

Possibilistic C-Means (PCM) clustering algorithm exhibits the robustness to noise, but the spatial information is not considered in this algorithm. Due to the effect of speckle in Synthetic Aperture Radar (SAR) images, the serious inaccuracies with segmentation can be resulted by using the PCM algorithm. A robust segmentation algorithm based on an extension to the traditional PCM algorithm is proposed in this paper. The relative location information and intensity information of neighboring pixels are introduced into the objection function of the PCM algorithm. The values of these information are determined by previous clustering result. The degree of influence of these information on clustering is optimized with Immune Clonal Algorithm (ICA), so the degree of influence is adjusted adaptively. Meanwhile, the clustering results of the PCM algorithm are optimized. In the paper, synthetic image and real SAR images are segmented to demonstrate the superiority of the proposed algorithm. The experimental results show that the proposed algorithm is insensitive to the initial segmentation result and improves the segmentation performance dramatically.

In this paper, a new Synthetic Aperture Radar(SAR) signal of chaotic phase modulated intra-pulse and random coded inter-pulse is porposed depending on the characteristic of extreme initial value sensitivity and pseudo-randmoness and multidimensional hyperchaos. Four hyperchaotic phase modulated signals are compared detailedly and hyperchaotic logistic map phase modulated signal is proved to be best for SAR transmit signal. This signal is proved with an excellent exhibition on encryption and high Electronic Counter CounterMeasures(ECCM) performances.

In this paper, a new SPICE model Multi-segment Multiple Transmission Line model (MMTL) is developed to model high-speed connectors based on Time Domain Reflection (TDR) measurements. This model is superior to MLC model in aspects of stabilization and efficiency. It is easy to be understood and optimized. Its accuracy can be under controlled. The excellent performance of the MMTL model is verified with experiments.

In this paper, a multi-waveguide output structure for gyrotron applications is proposed. Numerical simulations are performed for this structure by using High Frequency Structure Simulator ( Ansoft HFSS ). The results show that the energy conversion efficiency of more than 95.9% from the TE₀₁^○ mode to the TE₁₀^□ mode can be reached with the bandwidth of about 3% at VSWR of less than1.5 for the TE₀₁^○ mode input.

The formula is presented to solve the singular problem of Ludwig’s algorithm. And vector field is used as interface to combine Physical Optics (PO) and Uniform Theory of Diffraction (UTD) and MOment Method (MOM) to calculate the airborne antenna. The character of the array is analyzed with MOM, large and simple parts of the plane are analyzed with UTD, and the complex parts are analyzed with PO. The results show that combing these three methods together is a good way for the pattern prediction of the airborne slot array.

A small size and high efficiency HF broadband antenna that use wire sector-conical structure is designed. The Method of Moment is used to compute the VSWR and power gain of the antenna with different wire number, different size of feed-point gap and different sector-conical open angle. A sample antenna is built base on simulation results. The measured VSWR and radiation pattern agree well with those from simulation. The VSWR is within 2:1 over more than 95% of HF band, the average efficiency is 98% and the average gain is greater than 6dBi.

THz Electronic devices have the virtue of high power radiation, operating at normal temperature. They have potential applications in military, civil areas. This paper introduces in detail the recent development techniques and applications of THz electronic deivces, and gives some remarks on the developing trend of THz electronics devices.