A high-efficiency broadband polarization converter based on metasurface is proposed in order to broaden the working bandwidth of the polarization converter in terahertz band as well as improving the polarization conversion ratio. By adding a couple of resonating branches, the original single resonating point is increased to two, dramatically increasing the working bandwidth of the polarization converter. The low co-polarized reflectance is acquired through the characteristic of high-resistance surface when the metasurface is under electro-magnetic resonance, which could enhance the overall polarization conversion rate. The simulation results illustrate that this structure is able to achieve high polarization conversion in 0.401-0.555 THz with conversion ratio above 95%. The mechanism for high-efficiency broadband polarization conversion is discussed through simulating the reflect phase and surface current distribution. The dependence of the structure on the incident angle of terahertz waves is studied. The results show that this structure is able to maintain high conversion ratio at incident angle within 0°-40°. In addition, this design has advantage of simple structure. These works can help in the design of broadband efficient metasurface polarization converter.

Terahertz technology can be utilized to analyze the internal structure and thickness of layered materials due to its advantages of overcoming the limitations of traditional nondestructive testing techniques and penetrating ordinary nonmetallic materials. The working principle of terahertz time domain spectral system(THz-TDS) on transmission mode is introduced, the wave propagation in multilayer structure is described by using Rouard equivalent interface theory, and the theoretic transmission model of terahertz wave in the three layers of the medium is derived on transmission mode. The transmission imaging is conducted on the prepared samples through the terahertz time-domain spectroscopy system. The results prove that the internal information such as the location and shape of polyvinyl chloride(PVC) sheet can be detected, which can provide theoretical and experimental basis for detecting the internal structure of multilayer material.

Aiming to provide an accurate method to calculate the refractive index and absorption coefficient of solid powder materials in terahertz region, the effects of porosities of unary and binary powders on the extraction of optical parameters are studied by taking polyethylene(PE) and polytetrafluoroethylene(PTFE) as examples. Based on the effective medium theory, the refractive indexes of PE and PTFE are calculated by using Landau-Lifshitz-Looyenga(LLL) model, and the results are in consistent with the refractive indexes of thermoplastic plates of PE and PTFE. This research is help for constructing terahertz standard spectra database of solid powder as well as the quantitative identification.

Terahertz Time-Domain Spectroscopy(THz-TDS) technology is utilized to measure the spectra of morphine hydrochloride raw material, four excipients, intermediate and pharmaceutical in 0.2-2 THz. The characteristic absorption peaks of morphine hydrochloride raw material appear at 0.75 THz, 1.17 THz and 1.76 THz, and the THz spectra change from raw material to pharmaceutical. The absorption spectra of intermediates and pharmaceuticals are highly consistent, indicating that the coating has no significant effect on the THzspectra of pharmaceutical. Morphine hydrochloride molecules are calculated by Density Functional Theory(DFT), whose theoretical absorption peaks are at 0.84 THz, 1.10 THz and 1.50 THz. The theoretical spectra are in good agreement with the measured spectra. This work provides a theoretical and experimental basis for the rapid identification of drugs by terahertz technology, and has good application prospects in the establishment of terahertz fingerprint spectroscopy and rapid identification of morphine hydrochloride.

An S-band Relativistic Backward Wave Oscillator(RBWO) with lower magnetic field is designed in order to achieve the miniaturization of High-Power Microwave(HPM) systems. According to the characteristics of low magnetic field, the effects of slow wave structure, guided magnetic field, beam pressure, beam current, etc. on the output microwave are analyzed. The structure is optimized by using particle simulation software. On this basis, a low magnetic field S-band relativistic backward wave tube is designed, which has a guided magnetic field of 0.24 T, an electron beam voltage of 725 kV, a beam current of 6 kA, a frequency of 3.53 GHz, an output microwave power of 1.22 GW and a beam conversion efficiency of 27%. The preliminary experiment is performed on the accelerator platform with high current electron beam when the external magnetic field is 0.24 T. The microwave is output with average power of 1 GW, 3.58 GHz frequency and 90 ns pulse width. And a stability test at 1 Hz repetition frequency in 20 s is performed. The experimental results have laid a good foundation for realizing the relativistic backward wave tube of the permanent magnet packaging.

Radar data acquisition and storage equipment is an important equipment in radar system. It provides an effective method for off-line processing of Time of Arrival(TOA) of measured echo signal in engineering implementation. In this paper, the actual echo signal in radar acquisition and storage equipment is analyzed, and the TOA of Pulse Repetition Interval(PRI) detection method based on adaptive double-threshold is proposed, which can realize TOA detection of PRI in any echo data segment of time-sharing systems with a detection speed about 11ms. The TOA detection of Synthetic Aperture Radar(SAR) target echo based on sliding window method is proposed. The TOA of SAR target echo is effectively detected and verified by simulation.

Aiming at the requirement of high detection rate of target signal in the airport apron, the traditional target detection method is analyzed, and a mode S signal detection method with increasing falling edge decision is proposed. Furthermore, Genetic Algorithm is utilized to combine the stations with good reception performance to improve the detection rate. Compared with the common mode S signal target detection method, the receiver combination based on the improved method can obtain higher system detection rate. It can meet the requirement that the target area can calculate the target position in a probability not less than 99.9% with only 9 receiving stations. The simulation results of three-dimensional electromagnetic propagation model verify the effectiveness of the conclusion.

The tracking algorithm shows poor tracking effect when the moving target is occluded and the scale is changed. A discriminant scale space tracking algorithm combined with particle filter is proposed. Firstly, the target area of two adjacent frames is extracted, the structural similarity of the target area is calculated and compared with the updated threshold to determine whether the target is blocked. Secondly, if occlusion occurs, the particle filter algorithm based on color distribution is enabled to track the target, otherwise, the position filter in Discriminative Scale Space Tracking(DSST) is adopted to determine the target position. Finally, the scale filter is utilized to determine the target scale and the particle filter target model is updated according to the target scale. After the experiment on OTB2015 test set, the accuracy and success rate of the algorithm in this paper are improved compared with that of the mainstream algorithms such as DSST and Kernel Correlation Filter(KCF), especially the best tracking performance after occlusion occurs.

A two-step frequency fast acquisition and accurate tracking recovery scheme is proposed aiming at carrier frequency recovery in Orthogonal Frequency Division Multiplexing(OFDM) system. Firstly, the influence of frequency offset on receiver performance is analyzed based on semi-analytical method, and then the estimation algorithm of frequency offset based on maximum likelihood estimator is proposed. Finally, for coarse frequency acquisition, the scheme uses the known symbols of a single synchronization sequence as the data-aided acquisition. Once the acquisition is over, the circuit switches to a decision-directed mode to perform fine frequency tracking, so as to achieve reliable data demodulation. The performance of the acquisition algorithm is evaluated in terms of the expansion of the lock-in frequency range and the correct locking performance, while the tracking performance is evaluated in terms of bias and variance of the steady-state frequency error. Finally, the basic principles of frequency control loop design and the selective criteria of loop parameters in acquisition and tracking mode are provided, and the performance of the proposed frequency recovery system is verified by simulation.

A bistatic backscattering system architecture and its noncoherent modulation scheme based on Frequency Shift Keying(FSK) are proposed in order to realize the applications requiring large amount of wireless sensor coverage and large communication range. Firstly, the backscattering signal and the channel model for the bistatic backscatter system architecture are analyzed in detail. Then, on this basis, an FSK based noncoherent modulation and techniques to overcome carrier frequency offset introduced by the utilization of bistatic architectures are proposed for power-constrained cases. Finally, the receiver chains based on FSK and the Bit Error Rate(BER) calculation are provided. The experimental results show that the proposed bistatic backscattering architecture and its FSK based modulation and demodulation technologies not only have good BER performance, but also have the potential of large communication range, which is applicable for large-scale and power-constrained sensor networks.

Aiming to the problem that traditional nonlinear filters have bad robustness for abrupt state change system, the tracking is slow and even becomes invalid, Strong Tracking seventh-degree Cubature Quadrature Kalman Filter(ST-7thCQKF) is proposed. The algorithms fuses seventh-degree Cubature Quadrature Kalman Filter(7thCQKF), which shows good filtering effect for nonlinear system, with Strong Tracking Filter(STF), the tracking precision of abrupt state change system is improved through introducing fading factor into the prediction error covariance of 7thCQKF to adjust the gain matrix in filter process. The simulation and experiment results show that, ST-7thCQKF can well deal with the problem of state tracking for system with abrupt state.

In order to improve the localization accuracy of Wireless Sensor Network(WSN) nodes, a Density-Based Spatial Clustering of Applications with Noise(DBSCAN) clustering weighted localization algorithm based on Correction of Adjacent Anchor Node(CAAN) is proposed. Firstly, the algorithm selects three nodes from the anchor nodes within the communication range of the unknown nodes to form a triangle, and proves that the positioning error is the smallest when the unknown node is at the center of the circumscribed circle of the triangle. And the algorithm selects some appropriate anchor nodes according to this theory and combines with the filtered Received Signal Strength Indicator(RSSI) values for positioning. Then the DBSCAN clustering algorithm is adopted to remove the values with large errors. Secondly, the number of core points of the clusters is regarded as the weight, and the initial coordinates of the unknown nodes are calculated by the weighted location algorithm. Finally, the distances between anchor nodes coordinates and the initial coordinates are calculated, and the adjacent anchor nodes are selected to correct the initial coordinates, so that the final positioning results are more accurate. The simulation results show that the positioning accuracy of the proposed algorithm is improved by 69.55% and 38.64% compared with the weighted centroid location algorithm and the weighted centroid location algorithm based on RSSI ranging filtering optimization.

Self-organized wireless network, featured by non-centralized, multi-channel, multi-hop, meets the requirements of emergence networks and dedicated networks. To gain the network performance with longer range cover, non-visible communication and higher throughput, tri-radio nodes supporting IEEE802.11 ac protocol are selected. Combining with Better Approach To Ad-hoc Network Advanced(BATMAN-adv) routing protocol, a system of self-organized wireless network with multi-channel and multi-interface is realized. The field test data indicates that the system extends coverage to 5 hops with 30% throughput loss and the throughput is up to 300 Mbps with orthogonal channels under full duplex mode in 5 G spectrum.

A new type of ultra-wide band dual-polarized antenna with simple structure is presented. The antenna uses cross dipole antennas to generate dual polarization, each dipole antenna is composed of two octagonal rings. The stubs are loaded inside the octagonal ring to introduce new resonance frequency points, which greatly increases the bandwidth. The presented antenna has a compact structure with a planar size of only 0.3λL×0.3λL, where λL is the wavelength corresponding to the lowest frequency within the whole working frequency band. An antenna sample has been fabricated and tested. The measured results show that the antenna can achieve Voltage Standing Wave Ratio(VSWR)<2 in 1.24-4.42 GHz. The relative bandwidth is 125% and the pattern bandwidth is 95%(1.24-3.60 GHz). The directional radiation performance is good, and the gain in the pattern bandwidth is greater than 7dB.

The array pattern of Multiple Input Multiple Output(MIMO) antenna array has grating lobes due to the large array element spacing, and the false targets that affect the target recognition appear in the radar echo imaging. An improved genetic algorithm is proposed to optimize the array arrangement. The traditional standard genetic algorithm is improved to represent MIMO array with multiple matrix combinations, and the pattern sidelobes of sparse array with random distribution in rectangular plane are optimized. The method based on Logistic chaotic sequence is adopted to generate population disturbance and avoid the optimization process entering into the local optimal state. A uniform regular arrangement of MIMO array with 22 transmitting antennas and 22 receiving antennas and a modified MIMO array optimized by modified genetic algorithm are compared by examples. The results show that the modified genetic algorithm can effectively avoid the grating lobes in the regular array pattern, reduce the side lobes of the pattern, and improve the radar imaging performance. The optimization algorithm has strong practicability for its variable is controllable, which provides a solution for array arrangement of MIMO radar.

A time dilation drift tube is simulated by Particle-In-Cell(PIC) model, which can be used for measuring pulsed signal at least 10 ps for Full Width at Half Maximum(FWHM). The factors influencing the coefficient of spread are calculated including radius of photocathode, length of acceleration tube, acceleration voltage, length of drift tube, center magnetic field of solenoid，energy and current of photo electrons. Results show that a linear characteristic exists between the coefficient of spread and the energy and current of photo electrons, which means signal of time dilation drift tube is independent of initial pulsed electrons energy distribution and current waveform. The proposed time dilation drift tube offers a way to diagnose beam length parameter of inverse Compton scattering source instead of streak camera.

A design scheme of electromagnetic pulse radiation system is proposed. The system consists of a Marx generator, a chopping-peaking combination switch pulse forming line and a high-power ultra-wideband Transverse Electro-Magnetic(TEM) wave horn antenna with low-frequency compensation. The unipolar pulse generated by the Marx generator is formed into bipolar pulse by the chopping-peaking combination switch pulse forming line, and then fed into the antenna for radiation. The simulation results show that the electromagnetic pulse source can generate bipolar pulse with pulse width of 1.41 ns and peak power of 7.69 MW when the charging voltage is 10 kV. This bipolar pulse spectrum is mainly distributed in the frequency range of 0-1.6 GHz. The antenna bandwidth of high-power ultra-wideband TEM horn antenna is 0.625?2.9 GHz(the relative bandwidth is 129%) and the power capacity of the antenna can achieve 10 MW, which can effectively radiate bipolar pulses generated by electromagnetic pulse source.

A flame detection method based on entropy weighted Support Vector Machine(SVM) is proposed. Firstly, the three-frame difference algorithm is utilized to improve the Visual Background Extractor(VIBE) algorithm, and the Three VIBE(TH-VIBE) foreground detection algorithm is proposed to improve the accuracy and integrity of the acquisition of the suspected flame area. Secondly, entropy weighting is adopted to reduce the redundancy degree of feature data such as texture feature, area change feature, roundness feature and gray level feature, and an entropy-weighted flame recognition model is established to improve the flame recognition rate and accuracy. Finally, based on the flame data from Keimyung University in South Korea and SPG working group of Bilkent University in Turkey, the flame detection accuracy can reach 97% with high robustness.

A Dynamic Spectrum Allocation(DSA) method is proposed to solve the problem of low utilization of wireless spectrum resources based on Modified Cloud Quantum Genetic Algorithm(MCQGA). The method can adjust the rotation angle of the quantum gate dynamically, and uses the cloud theory to cross and mutate. According to the graph theory coloring model, the maximum sum of mean reward, the maximum minimum bandwidth and the maximum proportional fairness measures are considered for spectrum allocation. Particle swarm optimization algorithm, traditional genetic algorithm and basic quantum genetic algorithm are selected for comparative simulation experiment. Simulation results show that the proposed method is more suitable for spectrum allocation.

In view of the complementary advantages of different focus images for the same target and the problems of unclear focus, blurred edge and ghosting in the existing multi focus image fusion algorithm, a multi-focus image fusion algorithm based on Parameter Adaptive Pulse Coupled Neural Network (PAPCNN) and Convolutional Sparse Representation(CSR) is introduced. Based on the decomposition of high-frequency and low-frequency coefficients by Non-Subsampled Shearlet Transform(NSST), the low-frequency coefficients are fused by CSR, and the high-frequency coefficients are fused by a Parameter Adaptive PCNN(PAPCNN) algorithm. The implicit function β in PAPCNN is improved to achieve better fusion effect. The experimental results show that the proposed method solves the problems of the traditional PCNN algorithm, such as the difficulty of setting parameters in image fusion and the poor performance of the traditional sparse representation in detail preservation. It has greater advantages in visual effect and objective indicators compared with the existing mainstream fusion methods.

A new image content forgery detection algorithm by means of energy constraints and structure similarity clustering mechanism is proposed. Firstly, with the help of Hessian operator, a box filter is utilized to generate row Hessian formulation to accurately detect image features. Then, by calculating the Haar wavelet value of the image, the direction information of the image is obtained to construct the neighborhood window of the image features. Then the curvature information of the pixels in the neighborhood window is calculated to form a robust eigenvector. Finally, Euclidean distance measurement is adopted to measure image features, and regional energy features are combined to complete the constraints of measurement results, so as to achieve accurate matching of image features. Structural Similarity Index(SSIM) function is utilized to identify forgery areas by clustering matching results, and accurate detection is realized. The simulation results show that, compared with current content detection technology, the proposed algorithm has higher detection accuracy and robustness under the interference of various geometric transformations.

In Smart Grids(SG), measured user data in Smart Meter(SM) in residential area are sent to Control Center(CC) passing through a few intermediate nodes. Hence, privacy preserving of user data is one of the biggest challenges in smart grid researches because the habits and behaviors of users can be disclosed by data mining the User-Related Data(URD). A Privacy-Preserving Data Aggregation(PPDA) algorithm is proposed. In PPDA algorithm, the Group Location Privacy(GLP) approach is taken advantage to mask fine-grained user data generated by SMs, and Paillier encryption system is utilized to preserve the user data privacy. The proposed protocol does not need any secure channel. The security and performance analysis shows that the proposed approach is secure against eavesdropping attack and collusion, and its computational overhead is acceptable compared with that of the previous works.

The current defuzzy method which only uses the sparse feature of the image as the prior information has poor defuzzy performance induced by ignoring the effect of false edges (such as ring defects) on the point spread function estimation. A regularized image deblurring algorithm with total variation under the constraint of ringing is designed based on the prior information of the complex structure image. Firstly, the multi-resolution image pyramid strategy is adopted to build a multi-layer image model, and the prior information of ringing is obtained by comparing the blurred image with the potentially clear image. Secondly, the ringing regularization constraint term is integrated into the total variation method to build a multi-regularization deblurring model, and then the variable separation method is utilized to transform the deblurring model into a multi-function optimization problem. Finally, the first-order original-dual algorithm is employed to solve the Point Spread Function(PSF) and clear image in the order from low resolution to high resolution. Experimental results show that compared with the current image deblurring technology, the proposed algorithm has a more rational deblurring effect, and the recovered image shows higher peak signal-to-noise ratio and structure similarity, which can better preserve the image edge and texture information.

In order to solve the problem as low location and detection accuracy of duplicate content areas induced by ignoring the color information and the correlation between different color components in current image forgery detection method when identifying the duplicate content area, this paper designs an image forgery detection method based on improved Speeded Up Robust Features(SURF) descriptor and multi-polarity complex exponential transformation. The Gaussian low pass filter is introduced to filter the color image for eliminating noise. Then the color invariance of the filtered image is calculated, and the gray component of the SURF descriptor is replaced by the color invariance to improve the SURF method for obtaining a new Hessian matrix and detecting the interest points in the color image adequately. Subsequently, a set of connected Delaney triangular networks is constructed by using these interest points. The local visual features of triangular networks are extracted based on the quadripolar complex exponential transformation. The Euclidean distance between visual features is calculated, and the triangulation mesh is registered according to the preset threshold. Finally, random sample consistency is introduced to eliminate mismatched triangular networks, and post-processing method is defined to locate the duplicated and forged regions. The test data show that compared with the existing copy-paste forgery detection methods, the proposed method has higher accuracy in forgery detection under various geometric transformations.

A new Distributed Fault Detection Algorithm(DFDA) is proposed to solve the node fault problem in wireless sensor networks. The DFDA algorithm uses the node degree information to estimate the importance of the node to the network, and saves the node with high node degree to the network as much as possible. The fault nodes are detected by comparing the sensing data among nodes. In order to enhance the accuracy of the detection, a double determination strategy is adopted. The simulation results show that the DFDA algorithm improves the accuracy of detecting fault nodes and reduces the false alarm rate compared with similar algorithms.

The movement of nodes challenges the design of routing in Mobile Wireless Sensor Networks (MWSNs). Therefore, Contact time-Energy Consumption Area(CECA) based Routing is proposed in this paper. In CECA routing, all the nodes follow a sleep-wakeup pattern to improve energy efficiency. Communication between the source and the sink is established by creating a rounded rectangle region. Only the nodes in rounded rectangle region participate in the routing. The Contact-Time(CT) between source and neighbor node is computed by mobility information, and the timer is set by CT. The next-hop forwarding node is selected by timer. Simulation results indicate that CECA protocol has better performance in term of packet delivery ratio and connection-time of routing.

Density Peak Clustering(DPC) divides the data according to the density and distance attributes of points, which can achieve better clustering results for most data sets. However, the nearest neighbor allocation method of DPC will cause large errors for the data sets with overlapping. Aiming at this defect, a multi neighbor voting clustering method is proposed, which uses the voting results of multiple neighbors to determine the ownership of unknown points. Numerical experiments show that the density peak clustering algorithm based on voting method outperforms general DPC when facing overlapping data sets.

Data Transfer Rate-based Routing(DTRR) is proposed for Delay-Tolerant Networks(DTNs). Each message is divided into several message blocks. When the source node meets the appropriate forwarding node, it transmits the message block, otherwise it stores the message block in the cache. At the same time, the DTRR combines the contact frequency, the duration of the contact and the available space of the cache area to deduce the message transmission rate of the link. The next hop forwarding node is selected according to the message transmission rate. Simulation results show that the proposed DTRR has better performance in message transmission rate than similar Spray-and-Wait Routing(SWR).

Based on the V58300 hardware platform independently developed by the Institute of Microelectronics of the Chinese Academy of Sciences, an integrated circuit function test system is designed and implemented. The system includes two parts: host computer and slave computer. By changing the definition of the I/O related to the test system and the input test vector file in real time on the host computer, the functions test of Dual In-line Packaged(DIP) integrated circuits with various operating frequencies of 25 MHz and below and I/O numbers of 48 and below can be automatically completed. The system realizes the universalization and low cost of the test system. Finally, it is proved that the test system can effectively test related chips by experiments.

Based on the introduction of Chua's periodic table, the position of the existing circuit elements(resistor, capacitor, inductor, memristor, memcapacitor, meminductor, fractor and fracmemristor) in the periodic table are given. In recent years, the concept of Fractional Order Memristor(FOMR) has been developed, but the use of this name is not consistent. In this paper, the existing FOMR include circuit are summarized into four types, and the locations of the elements in Chua's periodic table are determined. Fractional integration is a powerful tool to represent memory loss. This paper not only gives the unified constitutive relation expressions for circuit elements, but also gives the definitions for fractional integral control type memory elements―Current Fractional integral controlled Memcapacitor (CFMC), Voltage Fractional integral controlled Memcapacitor(VFMC), Current Fractional integral controlled Meminductor(CFMI), Voltage Fractional integral controlled Meminductor(VFMI), and Current Fractional integral controlled Fracmemristor(CFFM), and Voltage Fractional integral controlled Fracmemristor(VFFM), etc. In addition, the operation structure diagrams of some fractional integral control memory elements are given, and their characteristic curves are analyzed theoretically.