Abstract:In this paper， we adopt the thoughts and methodologies of Shannon’s information theory and use the distance-amplitude and phase mutual information between the received signal and the measured object as a measure to propose a unified definition and description method of the target distance information and amplitude-phase information and derive their closed expression. Thus， we establish an information theory model for multi-carrier radar systems. Studies have shown that target distance information and amplitude-phase information will interact with each other， and amplitude-phase information usually depends on distance information. Besides， the amplitude-phase information of the target is only related to the SNR but not to the distance information when the scattering coefficient of the target obeys the complex Gaussian distribution. This paper further studies the relationship between the distance information of the target and the maximum likelihood estimation. Theoretical analysis and numerical simulation results show that the Cramer-Rao bound is an asymptotic upper bound for distance information at high SNR. However， the actual radar system usually works in the medium SNR environment， and its theoretical boundary is not clear for a long time. Now， the distance information of the target can be used as the upper bound of the maximum likelihood estimation， which provides a basis for the performance of the actual system. This conclusion reveals that radar information theory has an important guiding role for practical applications.

Abstract:To improve the traditional subspace data fusion （SDF） algorithm with multiple arrays in terms of degree of freedom （DOF） and accuracy， a direct position determination algorithm for non-circular （NC） signals with multiple arrays is proposed by exploiting the NC characteristics and the concept of reduced-dimension （RD）. Specifically， the NC characteristics are used to obtain the extended spatial information， which contributes to the extended array aperture and enhanced DOFs. However， this leads to the expensive high-dimension search. As a result， the concept of RD is introduced to discard the NC phase and then construct the RD spectrum search function based on SDF. Compared with the traditional SDF algorithm， the superiorities of the proposed algorithm in DOF and position performance are corroborated by numerical results. Besides， without losing the estimation performance， it significantly reduces the complexity.

Abstract:With the increasingly complex electromagnetic environment， for a receiver， especially in non-cooperative condition， identification and analysis of emitter sources are regarded as an important method to obtain electronic intelligence. Emitter identification refers to the process of extracting and analyzing characteristics of emitter signals intercepted by the reconnaissance equipment. The category and type of emitters is made. As a momentous direction in the electronic counter measures（ECM）area， emitter identification has a significant meaning as well as a wide range of applications in radio safety and spectrum resources management. Based on the analysis of a great deal of domestic and foreign literature，this article starts with the main characteristics of emitter identification in simplicity， then elaborates the classification and main methods of emitter identification. The actualities of emitter identification are introduced. Emitter data sets are categorized. This review ends up with possible future development trends in emitter identification.

Abstract:Combining the advantages of unmanned aerial vehicle （UAV） and millimeter-wave technologies， the UAV millimeter-wave （mmWave） communication system can provide high-speed data transmission and wide network coverage capability， which leads to a broad application prospect in military communication systems. The accurate channel model is vital for the UAV mmWave communication system design and performance evaluation. Different from the conventional mobile communication scenarios， the UAV mmWave communication scenario has obvious three-dimensional propagation characteristics. The key factors， i.e.， three-dimensional scattering space， three-dimensional flight trajectory and posture， three-dimensional array antenna and three-dimensional narrow beam， should be taken into account in the channel modeling. This paper summarizes the new requirements and challenges of UAV mmWave channel modeling， and then reviews the wireless channel modeling method and the research progress of channel models. Finally， the future development of UAV mmWave channel modeling and key technologies are given， which aims to provide reference for the scientific construction and standardization of UAV mmWave channel models.

Abstract:Aiming at the problem of poor shrinkage of the soft thresholding function in the projected iterative soft thresholding algorithm， a projected iterative p-thresholding algorithm is proposed. It replaces the soft thresholding function in the projected iterative soft thresholding algorithm with p-thresholding function， which will bring greater penalty for small coefficients and produce smaller bias for large coefficients to suppress the noise and reduce reconstruction errors. To speed up the algorithm， using the Nesterov gradient acceleration technology， a projected fast iterative p-thresholding algorithm is designed for magnetic resonance image reconstruction. When the tight frames are shift-invariant discrete wavelet transform and Contourlets， the projected fast iterative p-thresholding algorithm is used for compressed sensing magnetic resonance imaging. Compared with the smoothed fast iterative soft thresholding algorithm， projected iterative soft thresholding algorithm and alternating direction multiplier method， simulation results show that the projected fast iterative p-thresholding algorithm promotes the reconstruction speed and the reconstruction quality of magnetic resonance imaging. And the influence of the p value on the performance of the algorithm is analyzed， and a suitable p value selection method is given to obtain a better convergence speed and reduce the reconstruction error.

Abstract:Under the application background of interference search in space-based positioning system based on light Unmanned aerial vehicle （UAV）-platform， the implementation mechanism of multi-platform time difference positioning （TDOA） is analyzed in detail. In order to solve the problem of UAV group arriving at the optimal positioning area quickly before TDOA location， and then realizing effective positioning， a TDOA positioning solution based on received signal strength （RSS） positioning auxiliary information is proposed， and the whole positioning process and key scenarios are described in detail. Through the feasibility demonstration of the method and the analysis of the positioning performance， it is concluded that this method can make the maximum time of the whole positioning process controlled within a continuation cycle of the unmanned machine， under the premise of the smooth implementation of the automation of the positioning process.

Abstract:In a single-cell system where the base station and multiple users are multi-antenna hybrid beamforming architectures and the channel is an ideal millimeter-wave channel， aiming at the problem of maximum total spectral efficiency， a low-complexity hybrid beamforming algorithm is proposed. The program uses a step-by-step approach. First， the analog beamforming matrix of the base station and the mobile station is solved respectively. Baseband channel is obtained based on the analog beamforming matrix. Then the block diagonal digital beamforming algorithm is used to get the digital beamforming matrix. Simulation results show that， compared with other schemes， this scheme also improves the overall spectrum efficiency of the system while reducing the complexity.

Abstract:The radar signals of polyphase codes are similar， which is easy to be confused under low signal-to-noise ratio （SNR）. The classic Choi-Williams and other time-frequency distribution methods constrained by the time-frequency resolution are difficult to characterize the details of polyphase codes. Here， we propose an automatic recognition method based on the short-time Fourier transform-based synchrosqueezing transform （STFT-SST） and deep convolutional network. On the feature selection， the STFT-SST is used to radar signals for time-frequency analysis， and a spectrum enhancement algorithm is proposed to enhance the time-frequency features under low signal-to-noise ratio， then the high-resolution feature images are obtained. On the classification network， a nine-layer deep convolution network is designed， and the inception module is introduced to capture the signal’s detailed features. The simulation results show that when the SNR is -8 dB， the average recognition rate for five polyphase codes reaches 91.8%. The recognition performance of the proposed method is better at the low SNR.

Abstract:To improve the prediction speed and accuracy in indoor localization， a novel algorithm based on hybrid clustering and LASSO is proposed. Coarse localizer is taken by clustering matching and LASSO theory is used for fine localization. Besides the traditional received signal strength （RSS） based clustering， a coordinate-based clustering method is also used aiming at reducing the error caused by wrong cluster match. The similarity of the RSS coverage vectors is used as the criterion of clustering and cluster matching to reduce the computational complexity. The algorithm of LASSO is applied to recover RSS signal from noisy measurements with reduced demand for power and memory. Experimental results indicate that the proposed algorithm leads to an improvement on the fine positioning accuracy and online complexity. An average positioning error of 1.73 m is achieved with grid spacing of 1.8 m.

Abstract:A calibration-free indoor positioning method based on depth feature mining is proposed to solve the problem of RSS difference and positioning accuracy offset caused by heterogeneous devices in indoor positioning based on WiFi location fingerprint. In the offline stage， the original fingerprint database is processed by the combination of the strongest access point （AP） classification and procrustes analysis， and the standardized sub-fingerprint database is acquired. Stacked denoising autoencoder （SDAE） is used to learn the standardized sub-fingerprint database to obtain the depth feature fingerprint and construct the depth feature sub-fingerprint database. In the online stage， the same fingerprint processing method as the offline stage is used to mine the depth features of RSS data， and the WKNN method is used to match the depth feature sub-fingerprint database to obtain the estimated position. Four different types of mobile phones are used in typical experimental building scenarios. Compared with the traditional standard fingerprint calibration methods， the positioning accuracy of the proposed method is improved by 5.9% and 12.5%， respectively. Experimental results show that the proposed algorithm improves the positioning accuracy and robustness.

Abstract:With the development of communication technology and the boost of intelligent terminals， mobile content consumption has been witnessed a significant increase. While people enjoy the multimedia entertainment experience brought by wireless network anytime and anywhere， it also brings great pressure to the cellular networks， especially the repeated transmissions of popular videos， which leads to the waste of network resources. The caching technology is considered to be an effective way to solve such problems. It stores popular videos in advance at the edge of the network in off-peak hours to relieve the pressure of network traffic during peak hours. To provide users with better content transmission efficiency， the buffer-aided relay network is proposed. Due to the limited buffer space of the relay node， it is necessary to study the allocation of buffer resources when the relay node needs to serve multiple users. To this end， this paper proposes a buffer resource allocation method for relay nodes. Firstly， according to the data arrival model and data processing model of the relay node， as well as the buffer overflow probability that the relay node can tolerate， the maximum buffer proportion contributed by the relay node is provided. Then， according to the user’s data arrival model and data service model， the expression between the user’s buffer overflow probability and the buffer portion is given. Then， an optimization problem is established to minimize the sum of user buffer overflow probability in the network， and the optimal buffer allocation method is presented. Finally， simulation results show that the proposed method can obtain a smaller sum of user buffer overflow probability than the uniform allocation method.

Abstract:Compared with the GSM network， the two-way authentication mechanism has been added to LTE， and the prevention and control of pseudo base stations are improved. However， due to the shackles of traditional hardware facilities， detection and tracking are expensive and the flexibility is insufficient. Not only that， with the upgrade of communication technology， pseudo base stations are more inclined to be intelligent and miniaturized， which is difficult to detect. In response to the above problems， based on the software radio technology， this paper improves the related pseudo base station identification algorithm and proposes a new LTE pseudo base station identification scheme： Acquiring a key cell of the base station by building a software radio platform and establishing an LTE downlink broadcast information receiving link Relevant information， and the base stationis is distinguished based on the consistent information recognition algorithm. The scheme selected two test scenarios， correctly detected the legal base station， and also detected the information of the pseudo base station， which verified the feasibility of the identification method in this paper. Combined with the advantages of software radio itself， the technology formed in this paper has the advantages of high system upgrade efficiency and cost reduction.

Abstract:The global representation model for multi-heterogeneous social networks （MHSN） is presented， and the user space and content space association models of MHSN are established， which can be used as a reference for the follow-up research based on MHSN. Furthermore， taking the detection of localized emergencies in MHSN as an example， this paper discusses the integration method of MHSN based on content space， and conducts experimental analysis of data collection and emergency detection in Weibo and Tieba. Taking the user interest mining of MHSN as an example， this paper discusses the integration method of MHSN based on user space， and conducts experimental analysis on data collection and user interest mining of Weibo and Tieba. The results show that the proposed methods of emergency integration detection and user interest integration mining for MHSN can effectively improve the effect of emergency detection and user interest mining.

Abstract:In order to scientifically and reasonably evaluate the power grid operation safety capability， this paper first adopts a comprehensive weighting method of the rank-related subjective weighting method and the index information amount to integrate objective weights for comprehensively determining the final weight of the grid operation safety capability evaluation index system. Then， an improved gray correlation comprehensive evaluation model with resolution coefficient is constructed. Finally， the safety capability of a power grid operation in six periods is evaluated， and compared with the traditional gray absolute correlation model. Results verify the validity and practicability of the proposed model.

Abstract:Frequency-modulated continuous-wave （FMCW） radars utilize the frequency difference between the transmitted signal and the received echo signal to calculate the target range， so estimating the beat frequency is an important procedure in FMCW radar. However， the interference of negative frequency component and the multi-frequency component deteriorate the accuracy of frequency estimation in practical application. In this paper， a new frequency estimation method is proposed for multi-frequency estimation， which is based on the Orguner method and iteration. The method can accurately estimate frequency only using three discrete Fourier transform （DFT） samples near every frequency component. Simulations confirm that the proposed method outperforms traditional alternatives both in noiseless scenario and Gaussian white noise scenario， and has lower complexity because of no windowing processing.

Abstract:Compared with high-resolution （HR） face image， the low-resolution （LR） face image recognition effect is poorer. Researchers have put forward several LR face recognition algorithms based on the canonical correlation analysis （CCA） and kernel canonical correlation analysis （KCCA） to solve this problem， which ignored the supervised information and the consistency information between different views. In this paper， we put forward a novel dimensionality reduction algorithm—consistent discriminant correlation analysis （CDCA） by virtue of the class information and consistency information of different views. Furthermore， we design a LR face recognition algorithm based on CDCA. Concretely， we extract the principal component features from HR and LR face images respectively， use CDCA to learn the characteristic projection matrix of HR and LR face， and realize LR face recognition with the help of projection matrix. The experimental results show the superiority of the proposed method on recognition effect and robustness compared with the existing LR face recognition algorithms.

Abstract:An improved partial Haar transform （PHT） algorithm is proposed in this paper to improve the convergence of the first filter W₁（k） in the dual filter structure （DFS）. In the new algorithm， the W₁（k） adapts using a PHT version of the input signal to decrease its length. The convergence of W₁（k） is further improved by optimizing the step size to minimize the a posteriori error. Finally， the normalized factor of the algorithm is calculated and maintained piecewisely to save computation. By increasing the convergence of the W₁（k）， the proposed algorithm requires less adaptations to achieve a delay estimation of the adaptive system， and the overall convergence of the DFS is eventually improved with the proposed algorithm. The simulation results in the context of echo cancellation indicate that compared with other traditional adaptive algorithms， the proposed algorithm is found to be more efficient in sparse system identification.

Abstract:Line segment detection is a fundamental task in the field of machine vision. Usually， the detection processes need various pre-processing， such as image filtering， edge detection and extraction， which have a significant impact on the line segment detection. To tackle this problem， this paper introduced a new concept named contour difference， and presented a new algorithm based on the difference to detect line segments. By use of the new difference， the process of line detection is converted to searching for local maximum in contour differences. The detection algorithm needs no any pre-processing on the input image beyond the calculation of contour difference. Experiments on gray scale field images show that the proposed method can localize most plants accurately， even in the inference of noise and blur.

Abstract:This paper analyzes the requirement of sampling clock jitter of high sampling rate and high resolution data acquisition system（DAQ）， and gives the relationship between clock phase noise and clock jitter. The HMC1035LP6GE frequency synthesizer chip is used as the main chip of the clock generation circuit with output clock jitter measured as 90 fs （integer mode， 2 500 MHz output frequency， 100 MHz input frequency， phase detector frequency 100 MHz， loop filter bandwidth 127 kHz， integral interval ［10 kHz， 10 MHz］）. The performance of the circuit in various working conditions is compared， and the corresponding design guidelines are given.

Abstract:When using Lamb waves to detect the damage of the plate structures， the classic minimum power distortion beamforming algorithm can obtain good damage imaging accuracy， but it still can not avoid the influence of dispersion effect on the imaging accuracy. And this algorithm has shortcomings such as complex spectral matrix inversion operation and inability to invert singular spectral matrix， which may reduce computing efficiency significantly. In order to solve the above problems， this paper proposes an improved minimum power distortion beamforming algorithm that is more suitable for Lamb waves detection. The proposed algorithm performs beamforming in the frequency domain to solve the dispersion effect on imaging result， meanwhile combines the least square recursion method and the diagonal loading method to invert the spectral matrix to improve computational efficiency. Experimental and simulation results show that the algorithm can effectively remove the impact of dispersion on the imaging results of damage， thereby effectively solving the problems of artifacts and low imaging resolution in the imaging results of traditional beamforming algorithm. This algorithm also solves the problem of difficulty in inversion of the spectral matrix， which reduces calculation time significantly.