Abstract:Photonic computing can offer huge bandwidth to overcome the electronic bottleneck of electronic circuits, and it also plays important roles in all optical networks. Integrated photonic waveguide is becoming one of the most promising resources to implement photonic computing due to the compact size, light weight, and low power consumption. Photonic differentiator and integrator based on integrated photonic waveguide attract more and more attentions in recent years. In this paper, we review several schemes of ultrafast photonic differentiator and differential equation solver employing integrated silicon cascaded or doped microring an d MechZehnder interferometer to realize high-order photonic differentiator, tunable fractional-order differentiator, high-order all-optical differential equation solver and all-optical constant-coefficient tunable differential equation solver. And they are one of the most important development directions of the optical differential and integral.

Abstract:Microwave photonics (MWP) is an emerging issue concering the interaction between microwaves and optical waves. A variety of photonic technologies are investigated to enable and enhance functionalities in microwave systems which are usually very challenging when using pure electrical solutions. A fiber Bragg grating (FBG) is one of the key photonic devices in microwave photonics signal processing due to its unique features such as flexible spectral characteristics, low loss, light weight, compact footprint, and inherent compatibility with other fiber-optic devices. The recent development in FBG-based microwave photonics signal processing applications is discussed, with an emphasis on microwave photonic filters, microwave arbitrary waveform generation, microwave spectrum sensing and real-time FBG sensor interrogation. The limitations and potential solutions of FBG-based MWP system are also discussed.

Abstract:Microwave photonic signal processing has drawn a lot of attentions in the past decades due to the distinct advantages brought by the photonic technology, such as broad bandwidth, large tunability, immunity to electromagnetic interference and capability to perform parallel processing. As compared with the conventional electro-optical phase modulation and intensity modulation, polarization modulation converts (Ratio frequency) RF signal to be processed to an optical parameter with two degrees of freedom (i.e.polarization). By connecting a polarizer to the polarization modulator, to remove one degree of freedom, the phase modulation and intensity modulation can be easily obtained. As a result, any microwave photonic signal processing based on phase modulation and intensity modulation can be realized based on the polarization modulation. If the output of a polarization modulator is split into several branches and in each branch a polarizer is incorporated, multiple modulation schemes can be implemented simultaneously, which can be used to achieve multichannel or multifunction signal processing. In addition, based on the single sideband polarization modulation, a high performance photonic microwave phase shifter can be realized, which can be further applied to implement phase coding, microwave filtering and beamforming network. This paper will establish a theoretical model of the polarization modulation and describe the principle of the polarization-modulation-based signal processing systems.

Abstract:Microwave frequency measurement and analysis plays a significant role in civil and defense applications. Recently, big challenges emerge as the operating frequency used or to be used in the communication, radar, and electronic warfare increases rapidly. Fortunately, with the development of microwave photonics, a series of photonic approaches and solutions are proposed for measuring the frequency of microwave signals. Thank to the advantages including large instantaneous bandwidth and strong immunity to electromagnetic interference, these photonic approaches can be regarded as emerging solutions both for theoretical research and field applications. Several classic photonics assisted approaches for microwavefrequency measurement, such as those based on photonic scanning, frequency to amplitude mapping, frequency to space mapping, frequency to time mapping, photonic compressive sensing, digitalized microwave frequency measurement, and so on, are introduced with theory and experimental results. Meanwhile, recen advances and applications in photonic microwave frequency measurement are reviewed and summarized. In addition, the corresponding prospects are also briefly discussed.

Abstract:Fast imaging techniques have important applications in many fields. An ultra fast surface microscopic imaging technique is proposed and demonstrated. This technique is based on the time space frequency mapping of ultrashort optical pulses. Based on dispersive Fourier transform and spatial dispersion devices, the optical spectrum is mapping on time and space domain separately. The image is reconstructed after a high speed serial single pixel photo detector. A one and two dimensional imaging system with the frame rate of 20.9 MHz, 22 μm and 55 μm spatial resolution is realized. Imaging experiments with standard resolution targets are successfully demonstrated. This technique is an effective method for ultrafast imaging and can be used for high speed surface inspection.

Abstract:High-resolution optical signal processing is highly required in various Frontier fields such as high-speed optical communication systems, microwave photonics systems and high-resolution optical computing. The fundamental functions are high-resolution control on optical spectrum, microwave spectrum and time-domain waveforms. High-resolution programmable optical filter is the best choice to realize the above functions, because it can directly control the optical spectrum by programmable optical filtering, control the microwave spectrum by flexibly filtering the microwave modulated optical spectrum, and control the waveform shape by frequency-manipulating combined with time-frequency mapping. Therefore,high-resolution programmable optical filter is the key instrument in optical signal processing fields. In this article, we review the implementation methods of different programmable optical filters, and specially introduce the research progress and key technologies of stimulated Brillouin scattering based high-resolution programmable optical filter.

Abstract:Large capacity, high frequency, multiple beams and processing transponder are the trend of new generation satellite communication systems. The conventional signal processing and transmission payloads in electronic domain have drawbacks such as bulky, heavy, susceptible to electromagnetic interference, low bit rate and narrow band. The microwave photonic technology to satellite communication systems will overcome the above limitations, greatly enhance satellite communication system performance and meet the requirement of industrial, civil and defense communication technology in future. The potential applications of microwave photonic signal processing in satellite payloads are presented and the development trend is also overviewed.

Abstract:An all optical sampling scheme using a single semiconductor optical amplifier is proposed for analog signal processing. The analog optical signal is sampled by the probe pulse train through the nonlinear polarization rotation arising in semiconductor optical amplifier. Conversion efficiency and total harmonic distortion are presented to evaluate sampling linearity. In the experiment, 40 GSa/s all optical sampling for 2.5 GHz analog optical signal is demonstrated with commercially available fiber pigtailed components. The results show that the fundamental conversion efficiency and the total harmonic distortion are 1.35 and 2.01% at the operating power of 5 mW, respectively. Further, 160 GSa/s all optical pulsed sampling for 10 GHz analog optical signal is also demonstrated. The proposed all optical sampling requires only one semiconductor optical amplifier and has low power consumption． Ｉt is simple and potential for photonic integration.

Abstract:Signal source is a key component in both transmitter and receiver of a radar system, and its property determines the performance of the radar system. The signal generation based on electronic technologies is limited in aspects of carrier frequency, signal bandwidth, and noise properties, which cannot meet the requirement for signals with high frequency, large bandwidth and low noise. Microwave photonics, as a newly arisen and promising technology, can generate high quality microwave signals and would find wide applications in future radar systems. The recent progress of radar signal generation by microwave photonic technologies is presented. The generation of high quality local oscillator signal based on optoelectronic oscillators, and the generation of linear chirped or phase coded microwave signals are discussed. Through the analysis of the above techniques, it is found that microwave photonic signal generation, with the advantages of wide bandwidth and immunity from interference, is one of the efficient ways to break through the bottleneck for current radar signal generation.

Abstract:Compress sensing (CS) is a recently developed approach for the acquisition of sparse signals. According to the CS theory, a spectrally sparse signal can be sampled with a sampling rate far lower than that required by the Nyquist theorem and recovered with a high resolution. Application of CS in the field of wideband signals acquisition is highly desirable as the sampling rate of analog todigital converters (ADCs) can be greatly lowered. More recently, CS for sparse signal acquisition based on photonic techniques has attracted much interest. The photonic techniques and components help to enlarge bandwidth. It makes the photonics assisted CS a promising method for the ultra wideband sparse signals acquisition. The recent developments of the photonics assisted CS in the application of sparse signal acquisition are reviewed. Research achievements by our group are also presented.

Abstract:Digital linearization techniques are proposed to compensate the inherent nonlinearity of radio over fiber (ROF) links. In respect to the characteristic of ROF links, which have centralized control units and simple remote access units, multi-dimensional digital predistortion for multi-band ROF downlinks is proposed. The maximum input Radio frequency (RF) power increase 3　dB, indicating the improvement of downlink power efficiency. A memory-free multi-dimensional digital predistorter involving nonlinearity orders up to 5 at twice of oversampling rate is presented for practical multi band ROF links. For uplinks, the linearization technique is proposed based on the acquisition of output third-order intercept point. The spurious-free dynamic range (SFDR) of 128.3 dB in 1 Hz bandwidth is achieved by using the technique.　A digital post-compensation technique based on blind estimation is proposed to linearize multi-band ROF uplinks, which gives the improvement of 3 dB dynamic range.

Abstract:Microwave photonic filters, which have attracted great research interest in the past few decades, are photonic subsystems carrying out functions of radio frequency (RF) filtering. Their advantages mainly include high bandwidth, low insertion loss, immunity to electromagnetic interference, etc. Quality factor (Q) value, which determines the performance of the frequency selectivity, is one of the most desired features of microwave photonic filters. Among various structures proposed so far to improve Q values of microwave photonic filters, multi-stage filters with cascaded structures have attracted lots of interests, which can increase the Q values greatly. The newly proposed structures on ultrahigh Q IIR microwave photonic filters with architectures of cascaded multi-stage filters are reviewed. Future directions of research in this area are also discussed.

Abstract:Attitude determination and structural health monitoring system based on GPS multi-antenna has the advantages of fast speed, high precision and continuous working. However, the conventional systems usually use cable to connect antennas and receivers. A GPS-over-fiber multi-antenna receiver system is experimentally demonstrated. Thanks to the advantages of small size, light weight, low loss and immunity to electromagnetic interference of the optical fiber, the proposed system can achieve longer baseline and larger measuring areas than conventional systems. Parallel decoding algorithm is also applied in the proposed system. It can avoid cycle slips introduced by the signal switching in the conventional GPS multi-antenna system. The complexity of data processing algorithm is thus reduced and the efficiency and measuring precision are improved significantly. Experimental results show that the proposed GPS-over-fiber multi-antenna receiver system can measure the baseline accurately and the measurement error is only a few millimeters. The system can be potentially applied to attitude determination and structural health monitoring.

Abstract:To solve the low accuracy of fire situation assessment, fire alarm and fire source localization during fire detection in lager room for regular fire monitoring system due to fire monitoring node isolation, a fire detection and localization algorithm for large place based on wireless sensor network is proposed. The artificial neural network is firstly trained by fire data from wireless sensor nodes, and the artificial neural network with fuzzy decision is then used to estimate and decide the fire situation. The limited space smoke diffusion model and the gas temperature diffusion model are applied to locate fire source and measure the coverage of fire, and it is possible to assess fire situation more accurately in large room. It can provide more information for firefighters to take measures. The simulation results show that not only single node fire alarm based on neural network has high fire alarm probability but also total fire detect wireless sensor network has high accuracy on fire situation assessment and fire source localization. Theory analysis and experimental results show that the fire detection and localization algorithm is feasible.

Abstract:The test bed of digital multi input multi output (MIMO) radar in sub array level is developed and realized. Orthogonal binary phased shift keying signals are exploited in the subarray level. The transmit and receive digital beam forming is implemented in the receiving channel, and the observation of civil aircraft is accomplished successfully. The complexity of system design reduces greatly with the implementation of the orthogonal transmitting wave and multi beam techniques in subarray level, which is promising for engineering application. The MIMO radar function can be utilized as a kind of typical working mode in the digital array radar.

Abstract:Since non-permutative quantum gates have more complex rules than permutative quantum gates, direct use of non-permutative quantum gates can greatly increase the complexity of the synthesis algorithm, so given quantum gates should be used to create new permutative quantum gates, and then these permutative gates are used to synthesize the desired quantum reversible logic circuit, thus improving the algorithm performance. This paper focuse on how to use non-permutative quantum gates to construct new permutative gates, therefore, we absorb the idea of Gray code and present an efficient recursive construction which can use controlled-NOT gates and controlled K-th-root-of-NOT gates (non-permutative quantum gates) to construct the optimal Toffoli-like gates (permutative quantum gates).

Abstract:Band selection is an effective method for dimensionality reduction. However, the information from the small size of labeled samples usually misleads the supervised band selection. A semi-supervised band selection method based on graph Laplacian and self-training idea is proposed. The method first puts forward the graph-based semi-supervised criterion for feature ranking to generate the initial band subset. The graph Laplacian used in the criterion is refined with aid of the label information. Then, the supervised classifications are carried out based on the band subset and some unlabeled samples with higher confidence values are added into the labeled sample set. Afterwards the band subset is updated according to the feature ranking based on the newly generated labeled and unlabeled data, and is used for classification. The process repeats to obtain the final subset. The experiments on hyperspectral data sets are carried out compare several unsupervised, supervised and semi-supervised band selection methods. Results show that the proposed method can produce the band subset with better performance.

Abstract:In the orthogonal frequency division multiplexing(OFDM) system with IQ imbalances, a time domain least square (TD-LS) algorithm is proposed to estimate channel and IQ-imbalance parameters. To further exploit the sparsity of wireless channel, iterative shrinkage (IS) and parallel coordinate descent (PCD) are combined with the proposed TD-LS to form a new joint channel estimator TD-LS-IS-PCD. Simulation result shows that, in terms of bit error rate (BER)， the proposed TD-LS and TD-LS-IS-PCD algorithms perform much better than the traditional frequency domain least square (FD-LS) when the same least square equalizer is adopted. Furthermore, the BER performance of TD-LS-IS-PCD approaches that of the ideal channel estimator.

Abstract:Randomness tests of cryptographic algorithm is analyzed. In order to test and identify Zigbee protocol security of cryptographic algorithm in the internet of things(IOT), test modes are organized and divided combining with the characteristics of Zigbee networks and binary matrix rank theory test, and randomness tests method of Zigbee protocol are proposed based on matrix probability test. The method solves the one sidedness of binary matrix rank test to simply judge random sequence by linear correlation. It can determine whether the Zigbee protocol encryption mechanism and encryption strength are implemented or not. Simulation results show that th is algorithm has less errors, and higher reliability, which is much more convincing. The proposed method provides theoretical and practical guidance for information security evaluation of IOT.

Abstract:According to large-calculation and lower-efficiency of the auxiliary particle filter, an auxiliary marginal particle filter algorithm is proposed based on fast Gaussian transform (FGT-AMPF). Assuming that the state noise is additive and Gaussian, the solution of Chapman-Kolmogorov equation (CKE) for nonlinear filtering, is similar to executing kernel density estimation (KDE). Then FGT of KDE is introduced to improve the calculation efficiency. The simulation results show that the calculation error obtained by the conventional particle can also be gotten by using a small number of particles, and the algorithm greatly improves the calculation efficiency.

Abstract:For cognitive users with low SNR at transceiver front-end, a cooperative spectrum sensing algorithm based on truncated sequential probability radio test (SPRT) is proposed to improve the sensing performance. A plit-phase processing method is employed firstly. A split-phase processing method is employed by all collaboration cognitive radio（CR）nodes firstly, which divided the receipt signals into a number of segments. The cognitive radio nodes do a count of its local energy-based sensing in their various segments and compared with the specified threshold consequently. Instead of sending all the sensing results of cooperative CR user, only the number of sampling points bigger than the threshold is sent to fusion center serving as local detection statistics. It greatly lowers transmission overhead on common control channel. Gaussian distribution is approximately obtained based on DeMoivre-Laplace theorem and central limit theorem, so the computation complexity and the deriving process of likelihood ratio function are reasonably simplified. Theoretical analysis and simulation results indicate that compared with existing energy-detection sensing method, the proposed algorithm respectively reduces the average sample number around 55.86% and 37.51% under the conditions of H0 and H1 while the average SNR of CR users is -15 dB.

Abstract:Multihop range-free localization method is an effective and simple method to determine node location. However, it is generally suitable for isotropic and the node intensive network. Since the low performance of multihop range-free localization method in anisotropic networks, an improved scheme is proposed based on canonical correlation. This method obtains a high precision mapping model by canonical correlation regression between nodes hops and Euclidean distance, then obtains the estimated distance between unknown node and known node using the measurement of hop-count. It also solves the problem of multi-hop range free localization method, which the performance is low in anisotropic network. Experimental simulation results show that this method achieves higher accuracy and stability than other location algorithms.

Abstract:In the most existing connected dominating set (CDS) based coverage algorithms, the mechanisms of maximizing sleep node numbers is adopted to save energy in WSN. Active nodes of WSN cause rapidly exhausts energy which leads to CDS failure and fade coverage. In addition, frequently activating other nodes speeds up network topology changes, and lead to the network convergence problems. A learning automata-based area coverage algorithm is proposed for WSN. d-CDS is adopted to construct network topology, and learning automata is used to select the optimal node of current sensors. Then the constructed CDS can be optimized, and the load balance of the active nodes is realized to improve network coverage performance. Finally, Simulation experiments are conducted to compare Gossip, ST-MSN and TMPO. The results show that, the proposed algorithm is superior to the three algorithms in network coverage rate and the residual energy of active nodes.

Abstract:Data acquisition for phased array based structural health monitoring is conducted according to direction in the certain scanning rang of the structure, which affects data acquisition easily by some external factors, such as, environment and the change of the environment and structure. Therefore, the non direction data acquisition for phased array damage identification imaging method is proposed. The same excitation signal is used for all sensors to generate the signals travelling in the structure. The health signals and the damage signals are obtained by the data acquisition method. The damage scattered signals are obtained by comparing the damage signals with the health signals. Based on the phased array theory, the time delay is added to the scattered signals in the signals emission process and the receiving process according to the direction and the sensors. The processed signals are drawn on 2-D mapped image. Experiment on the composite structure shows that the damage in the structure can be well recognized. The method utilizes non direction data acquisition. It can greatly shorten monitoring time and is not affected by the change of environment and structure.

Abstract:Aiming at the analysis and the recognization in intelligent surveillance system. Hidden Markov model (HMM) is applied to analyze abnormal events detection in surveillance system. The method extracts motive object by background substraction, encodes shape features, color and changes rate of frames for feature vector. In training, feature vector is applied to HMM to obtain parameters A and B. In detecting, the feature vector is input into the HMM to detect abnormal events. The experiment shows that the method can detect abnormal events quickly and accurately.

Abstract:A novel wireless positioning method is proposed based on joint Time of arrival-direction of arrival (TOA-DOA) estimation to substantially reduce the computational burden of typical high accuracy algorithm——Joint angle and delay estimation multiple siginal classification (JADE-MUSIC). This method first separates the processed signal vector to estimate TOA and DOA to reduce the size of the signal covariance matrix. Thus the eigenvalue decomposition complexity is reduced. It applies DFT to simplify the pseudo-spectrum computation and utilizes pseudo-spectrum summation to enhance estimation accuracy. Target positioning can be realized fast and accurately via only one base station. Theoretical analysis shows that this method is of much lower complexity, Matlab simulation results prove that this method achieves high estimation accuracy and good positioning capability.

Abstract:The information of drogue containing position and size are used to establish Kalman filter equations. The model parameters are set considering drogue′s motion features in refueling process and the object occlusion coefficient is introduced to complete the parameters′ adaptive adjustment. The next-time states of moving drogue are estimated by the model and the estimation is corrected by observation. The experimental results show that the algorithm can track the drogue stably in work distances. When non-target moving objects appear in the images or the drogue is obscured, the algorithm still has the ability of continuous tracking.