Self-mixing interference in broadband terahertz(THz) Quantum Cascade Lasers(QCLs) are studied by the transition matrix theory and rate equations method. Under weak optical feedback strength, with the target moving in uniform motion, the self-mixing signal changes in a sine-like waveform. It is found that the self-mixing signal of the broadband THz QCLs under weak feedback can be applied to range finding, imaging, and spectral measurement. Under strong optical feedback, the spectrum is affected by the optical feedback obviously, while new modes arise near the solitary modes. As a target moves in uniform motion, the self-mixing signal shows the same number of peaks as that in weak feedback case. Therefore, the broadband QCLs under strong feedback cannot be applied to spectral measurement, but it can be applied to realize micron-magnitude range finding and imaging under certain conditions. The study is helpful to the application of THz sensor technology based on self-mixing interference in broadband THz QCLs.

A dual frequency terahertz radar is designed based on the dual frequency terahertz gyrotron. The targets echo model including micro-Doppler information is established for the vibration, rotation and rolling targets. The simulation of micro-motion feature extraction is carried out by using the time-frequency analysis method. The simulation results show that the 0.11 THz radar and 0.22 THz radar have centimeter level detection ability for micro-motion feature extraction of vibration, rotation and roll. Under the condition of strong noise, the self-power spectrum time-frequency analysis can suppress the noise and improve the detection ability of micro-motion feature extraction. Through the cross-power spectrum time-frequency analysis of 0.11 THz and 0.22 THz radar echo baseband signals, the micromotion feature extraction of the same frequency is enhanced, and the noise is suppressed, which helps to extract micro-motion feature information.

A new low cut-off voltage ring cathode electron gun model is presented in this paper. On the basis of traditional Pierce electron gun and pole-controlled electron gun, the spherical cathode is divided into annular emitting cathode and non-emitting cone to achieve lower focusing pole cut-off voltage, reduce switching loss of modulator unit and increase the maximum modulation frequency. The results show that the cut-off voltage of the cathode can be reduced by half by the introduction of nonemitting cone under the condition of perveance 0.53 μP, the cut-off voltage amplitude is reduced to 600 V from 1 250 V, the modulation loss of the corresponding power modulator is reduced to 1/4, or the modulation frequency is increased by four times, which is of great significance to the improvement of electronic countermeasures and radar system performance.

The fishery companies have many ships and the operation team is not fixed. It is very costly to solve the problem of ocean-going broadband communication by installing satellite communication terminals on each ship. The fleets are divided into two types: command ship and task ship. During the operation on the sea, each group includes a command ship and a number of task ships. A mobile broadband multimedia communication network is established, supplemented by strategies such as multicast and automatic routing switching. The completed system can achieve broadband interconnection between any ship and between the ship and the command center. When the command ship and the mission ship form a random team, the link can be adapted, and the system does not need to be reconfigured. The broadband communication distance between the command ship and the mission ship is more than 20 km. The system can greatly reduce the construction cost and operation cost of the oceangoing broadband communication network of the fishery company.

Distributed Aperture Fully Coherent (DAFC) radar is a kind of new and overturning technology, which can achieve synthetized signal processing for N 3 Signal to Noise Ratio (SNR) gain and break the limit of power-aperture product of radar. Due to the long distance between units of the satellite radar system, the wireless phase estimation and synchronization become one of the key problems. A theoretical model of distributed radar phase synchronization is established in this paper. A new phase synchronization method in the circular way is also proposed based on phase error analysis. Compared with Principal-Subordinate method, it eliminates the restriction on center junction in DAFC, and improves the anti-interference ability and the robustness of the algorithm. The simulation results validate the effectiveness of the proposed method.

Unmanned Surface Vessels(USV) with only surge force and yaw moment available are typical under actuated system which cannot be stabilized by any time-invariant continuous state feedback control law. For the realistic underactuated USV, where the mass and damping matrices are not diagonal, based on additional controller and backstepping method, a smooth time-varying tracking controller is developed to track any straight and curved reference trajectories, and also confines the transient response performance within the allowable range. Firstly, the system is converted into a diagonal form by using state transformations and control input is simplified through feedback linearization theory. Secondly, the virtual controller is designed to stabilize tracking error, meanwhile, Barrier-Lyapunov Function(BLF) is introduced to ensure that the tracking error does not exceed the prescribed value. Thirdly, the additional control is designed to deal with the problem of underactuation. Stability analysis shows that the proposed control strategies can guarantee all the states in the closedloop system are uniform ultimate bound. Matlab/Simulink results illustrate the effectiveness of the proposed control design.

In recent years, cognitive radar techniques have been developed quickly. How to improve radar detection performance basing on the obtained sensing information has become hot topic. A cognitive target detection method during tracking stage is presented based on tracking information, in order to improve target detection and tracking performance. For the target during tracking stage, the target existence has been proved, therefore the tracking information can be sent to target detector to expect an improved detection performance. As to the proposed cognitive detection method, firstly, target motion characteristics are extracted from tracking information, and a predicted region is established for the next instant; secondly, detection thresholds in the predicted region are adjusted by using target prediction probability information, under the Bayesian criterion and constant false track rate; finally, cognitive target detection is accomplished. Numerical results indicate that the cognitive target detection method can significantly improve target detection and tracking performance.

The application of near-far field transform technology in target characteristics testing is studied. By performing near-field imaging processing, far-field calculation and reconstruction, and convolution integral correction on the simulation results of the aircraft model, the near-field scattering can be transformed into the far-field. At the same time, the near-far field transform technology can effectively solve the problem encountered when measuring the Radar Cross Section(RCS) under the conditions not satisfying the far-field. By RCS tests on metal conductor cylinders, missile models, conventional aircraft models, angle reflectors, etc., and comparing the RCS test results of the single cylinder compression field with that of the plane wave compression field, it is obtained that the near-far field transform technology is suitable for those targets using stealth reduction technology, showing the effects of correcting the measurement data to a certain extent and improving the test accuracy. Nevertheless, the near-far field transform technology is completely unsuitable for those targets without taking stealth measures.

The existing electromagnetic big data management method is single and unable to make full use of electromagnetic data. The concept of partition management is introduced. The electromagnetic data is partitioned by geographic attributes using a clustering algorithm and managed by the graph database. The knowledge graph entities are transformed from the electromagnetic clustering results, and then the entity relationships are extracted to explore potential relationships among electromagnetic data. Aiming at the problem of the difficulty and low efficiency of electromagnetic interference source positioning, an improved Received Signal Strength Indication(RSSI) positioning algorithm based on knowledge graphs and big data real-time processing technology is proposed. The experiment simulates the process of interference source location under real electromagnetic data, and analyzes the performance of single-target interference source and multi-target interference source positioning. The experimental results show that the proposed method for locating electromagnetic interference sources based on the knowledge graph is more effective than the traditional RSSI locating method, and its error is smaller.

Traditional algorithms based on eigenvalue decomposition such as Akaike Information Theory(AIC) and Minimum Description Length(MDL) criterion not only require a huge amount of computation, but also reduce the performance or even cannot correctly work under the condition of low SNR or few snapshots. A novel source number estimation method based on subspace analysis is proposed. Firstly, the subspace estimation of the signal is completed fast by using Multi-stage Wiener Filter(MWF), then the projection value of array signal covariance in subspace matched filters is calculated. At last, the number of sources is obtained by analyzing their orthogonality. The simulation results show that the proposed method has better performance than other algorithms mentioned above in the low SNR or few snapshots, and the amount of calculation is greatly reduced.

In the process of drawing a lane line map for a computer, it is necessary to accurately track the function requirements of the lane line in the moving background. A lane line tracking method is proposed by combining the frame difference method with the window search. Firstly, the image captured by the wide-angle lens is corrected by the checkerboard, and then the Region Of Interest(ROI) including the lane line is converted into a bird's-eye view by using the Inverse Perspective Mapping(IPM), and the white and yellow pixels are separately filtered by using Hue,Saturation,Value(HSV) and Red Green Blue(RGB). Secondly, the lane line is corrected with the angle between the lane line and the vertical line. According to the pixel density of the corrected picture, the starting point of the lane line is selected, and the entire lane line is extracted by the sliding window search method. Finally, the improved frame difference method is utilized to track the lane lines and standardize the lane line pixels according to the lane line standard. A large number of actual road driving tests show that the accuracy of this algorithm is 94.97%, which can accurately complete the tracking of lane lines.

In modern society, the utilization rate of new energy vehicles is getting higher and higher. Many cities begin to promote new energy vehicles. The government also begins to attach importance to the development of new energy vehicles. Therefore, it is necessary for the entire distribution network to predict the load of the short-term new energy vehicle charging station. In this paper, a model based on the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN) and Quantum Genetic Algorithm(QGA) -Elman is proposed to perform load forecasting on similar days new energy vehicle charging stations. Taking the historical data of similar days given by the new energy vehicle charging station as input parameters, the model is established to predict the load of the next day. The combination model is improved in reducing prediction errors, and the research problems have certain application value.

The bus master Direct Memory Access(DMA) controller is implemented based on the Kintex-7 series Field Programmable Gate Array(FPGA) platform in order to improve the system performance of Peripheral Component Interconnect express(PCIe) bus interconnection devices in the process of high-speed communication and reduce the consumption of Central Processing Unit(CPU) resources. The high performance data transmission between Personal Computer(PC) and FPGA via PCIe is realized. DMA test cases are designed through the Root Port simulation platform, and the simulation results verify the correctness of the PCIe interface logic. The actual transmission rate is tested through the master computer and driver, and the experimental results show that the measured highest transfer rates are 1 620 MB/s on write and 1 427 MB/s on read, which reaches 84% of the theoretical maximum. The design scheme bears the advantages of low cost and high reliability, and can meet the requirements of data acquisition with high performance and low delay.

Aiming at the bottleneck problems of traditional Wireless Sensor Network(WSN) nodes like limited energy supply and short network life, based on the latest achievements in the field of wireless energy transmission technology, a charging path planning algorithm based on improved Q - Learning Wireless Rechargeable Sensor Network(WRSN) is proposed. Firstly, the base station performs charging task scheduling based on the energy consumption information of each node in the network; and then mathematical modeling and target constraint setting are performed on the path planning problem. The mobile charging vehicle is abstracted as an agent, and its state set and action set are determined. The ε-greedy strategy is reasonably improved for action selection, and the relevant performance parameters are selected to design the reward function. Finally, the state space environment is explored through iterative learning to adaptively obtain the optimal charging path. The simulation results prove that the charging path planning algorithm can quickly converge, and has certain advantages in terms of network life, average charging times of nodes and energy utilization compared with the classic algorithms of the same type.

The Vertical Double-diffused Metal Oxide Semiconductor(VDMOS) device is one that uses multiple carriers, which bears the characteristics of fast switching speed, small switching loss,high input impedance, high operating frequency and good thermal stability. This paper proposes a design and manufacturing method of a 60 V planar gate VDMOS device. In the process of device design, a new structural scheme is proposed. By reducing the lithography of a terminal ring layer(Guard Ring Layer), the terminal structure and the active area structure are combined on one lithography. And a new passivation structure is designed to improve the terminal voltage in the terminal process. The Polyimide(PI) passivation process is utilized instead of the traditional nitride silicon passivation layer. The test results show that the product meets the design requirements. The design scheme of the new structure proposed in this paper is intended to provide a new design idea for the chip design of other specifications.