With the continuous increase of high power laser，the demand for real-time accurate measurement of laser power in practical applications is becoming more and more significant. The traditional laser power measurement mainly depends on absorption calorimeter. The absorption calorimeter has some common problems，including large volume，slow measurement speed and low measurement accuracy. As a result，it is not suitable for the real-time power measurement of high power laser.The radiation pressure power measurement can effectively solve those problems. Based on the principle of radiation pressure power measurement，this paper designs and develops a rediation pressure power measurement device which can measure laser power up to 6 kW in real time. The device measures the output power of high-power infrared laser at 1 080 nm. The power range reaches 1 kW to 6 kW，the resolution of measurement reaches 50 W，and the measurement stability is better than 1%. The device can meet the real-time and accurate measurement requirements of kilowatt high power laser. The device can monitor the laser power in real-time，and can evaluate the transmission loss. The device will have great research value in the practical applications including high energy laser processing，laser guidance and laser communication.

The study of elastomer collision processes is important for cushioning and vibration damping applications，but it is difficult to measure with general equipment because of the presence of rebound phenomena and the complexity of the process. A frequency-shifted photon Doppler velocimetry（PDV）using two laser sources is proposed to study the collision process of elastic projectiles. The magnitude and direction of velocity are obtained by analyzing the beat frequency signal，which is generated by the reference and signal beam provided by two lasers. The experimental results show that the velocity of the projectile decreased to zero within 0.1ms after impacting the steel plate，and several round-trip motions occurred 1ms after rebound.Errors due to laser frequency instability are reduced by monitoring the frequency difference between the two lasers.

In order to reduce the influence of temperature change on the application quality of semiconductor pumped laser，a temperature control system based on thermo-electric cooler（TEC）is designed in this paper. The system uses STM32 as the core controller，and determines the temperature difference between the target temperature and the actual temperature of the pump module through the temperature sampling and control module. It combines the TEC power supply module and the main circuit module，and uses the PID algorithm to provide the TEC with appropriate driving current to heat or cool it. The temperature of the pump module is changed by the way of heat transfer. The stability of the pump module temperature is ensured through closed-loop control. Experimental result shows that the temperature control accuracy of the temperature control system does not exceed ±1 ℃，which has good stability.

In order to suit the lidar ranging system，a wide-range time-to-amplitude converter（TAC）with adjustable range and resolution is designed. The TAC ASIC employs a counter in combination with an analog voltage ramp，which significantly expands the range. The circuit is designed in a 180 nm CMOS technology，with a single TAC channel area of 400 μm×260 μm. The conversion period and sampling period of the overall circuit are controlled by external signals，and the range and resolution can be adjusted to suit applications in complex environments. Simulation results show that the TAC has a range of 6.4 μs at 20 MHz operating clock，a measurement resolution of 50 ps，a differential nonlinearity of ±0.05 LSB，and an integral nonlinearity of ±0.8 LSB. The TAC has good performance and is suitable for wide-range lidar ranging system.

For the purpose of shaping terahertz Gaussian beam transmitted by the terahertz transmitter into a terahertz sheetlike flat-top beam，this article proposes a method of designing which combines a dual-phase plates with a terahertz lightsheet to shape beam. In theoretical design，we first use the input-output algorithm to design a dual-phase plates that can shape Gaussian beams into flat-top beam，and then shape the flat-top beam to a sheet-like flat- top beam through terahertz light-sheet. Numerical simulation was conducted and an experimental system was built at the same time of theoretical design. The results all indicate that the system can convert the Gaussian beam transmitted by 0.33 THz terahertz transmitter into a flat- top beam with a sheet-like distribution in space. The relative root mean square reaches 71.41% for the sheet-like flat-top beam obtained in this experiment which fully demonstrates the effectiveness of the design.

Two-dimensional phase unwrapping algorithms are widely used in optical metrology-related fields. However，complex environments such as high noise and phase discontinuity in practical application scenarios often lead to the failure of traditional phase unwrapping. In this paper，a method based on deep convolutional neural network（DCNN）is proposed for phase unwrapping，which considers phase unwrapping as a multi-pixel classification problem and introduces an improved ResUNet segmentation network to recognize the categories，and after the segmentation is completed，the unwrapped phase map is combined with the segmentation result to generate the unwrapped phase. Once the segmentation is completed，the unwrapped phase can be generated by combining the parcel phase map and the segmentation result. In this paper，we compare with the existing methods on simulation datasets for the noise and discontinuity cases，respectively，and the phase unwrapping RMSE is only 0.006 2 for the wrapped phase map with -2 dB noise level，and for the phase discontinuity case，the RMSEm and RMSEsd are 0.001 7 and 0.017 8，which are much lower than ResUNet and several other methods.

Li doped CuO films are prepared on glass substrate by pulsed laser deposition，and the effect of Li doping on the structure and properties of CuO films is studied. The crystallinity of CuO films becomes better when Li doping concentration increases from 0 wt% to 2 wt%，and then becomes worse when Li doping concentration increases from 2 wt% to 3 wt%. After doping Li，the carrier concentration increases by at least three orders of magnitude，and it shows a trend of first increasing and then decreasing. The change of mobility is just the opposite. When the doping concentration is 2 wt%，the carrier concentration reaches the maximum，which is 1.10×1019 cm-3，and the resistivity is as low as 76 Ω·cm. This is mainly due to the fact that Li atoms enter different lattice positions of CuO when doped with different concentrations of Li.The electrical and optical properties of CuO thin films doped with Li have been improved to some extent，which provides theoretical guidance for further research of CuO thin film solar cells.

Aiming at the problem of brush wear of DC brush motor，a method of predicting and estimating brush state using particle filter algorithm is proposed. The dynamic model of DC motor is built，the brush wear process is simulated by changing the resistance value of armature winding，and the average current data of the brush wear process is simulated.According to the fitting results of the average current data，a basic model of brush state evolution is established. The unknown parameter b of the model is iteratively estimated by the particle filter algorithm of random resampling，and the value is stable near the truth value 0.002. The predicted model reflects the wear process of the brush more accurately，and can estimate the remaining service life of the brush，which is of great significance for the maintenance of the motor brush.

With the rapid explosion of data traffic and dynamic changes in bandwidth，the current fixed grid transmission system architecture is no longer able to meet the requirements. For the next generation high-speed elastic optical network transmission system，the article focuses on two issues：filtering bandwidth and fiber input optical power. The influence of the filter bandwidth on the performance of the next-generation high-speed elastic optical network system is analyzed through simulation transmission. The results show that the filter bandwidth for the next-generation high-speed elastic optical network system should not be greater than 105 GHz. The simulation transmission analysis shows that the influence of the filter bandwidth on the performance of the transmission system is consistent with the actual experiment by building different transmission systems. In order to study the optimal single wave input optical power of the next generation high-speed elastic optical network transmission system without causing significant fiber non-linearity costs，a real-time transmission system is built. The impact of different wavelength input optical power on performance is compared and analyzed through experiments. The results show that +5 dBm is determined as the optimal single wave input optical power for the next generation high-speed elastic optical network system with single carrier transmission rates of 400 Gb/s and 800 Gb/s.

To address the issue of the transmission characteristic curve of electro-optic intensity modulators being prone to drift due to environmental influences，this paper proposes a bias control method based on an improved particle swarm optimization algorithm. Based on the structural characteristics of the Mach-Zender electro-optic intensity modulator，the transmission characteristic curve of the modulator is derived. The effects of different bias voltages and RF amplitudes on modulation performance are simulated and analyzed. The optimal linear working point of the Mach-Zender electro-optic intensity modulator is determined to be ±Quad point. Then the principle of traditional particle swarm optimization is introduced. In order to optimize the performance of particle swarm optimization in bias automatic control problems，improvements are made to the particle swarm algorithm by dynamically adjusting inertia weights and particle swarm individual distribution，constructing specific fitness functions，and optimizing multi-objective parameters. Finally，the performance of the improved particle swarm optimization algorithm in bias automatic control problems is simulated and analyzed. It can accurately find the optimal linear working point and has a fast convergence speed. At the same time，the algorithm is transplanted to a self-developed bias control board. Comparative experiments are designed to prove that the improved particle swarm optimization algorithm can effectively track the drift of the bias curve. The amplitude change of the modulated output signal waveform does not exceed 2%，which meets the requirements of long-term use.

Inertial/satellite integrated navigation is an important means for shipborne inertial navigation to achieve longterm high-precision navigation. It can achieve real-time estimation and closed-loop of inertial navigation errors，ensuring high-precision navigation information output by inertial navigation. However，satellite navigation is susceptible to deception and interference，resulting in inaccurate navigation errors estimated by inertial navigation. When inertial navigation switches from integrated navigation state to autonomous navigation state，the navigation accuracy performance drops sharply. This article designs a method for preventing deception and interference in satellite navigation on the device side，using inertial/satellite integrated navigation filtering innovation to construct Chi-square statistics to detect the effectiveness of satellite navigation. Based on the detection results，the reference position information provided by satellite navigation is selectively used，so that the navigation error estimated by inertial navigation is not affected by the quality of satellite information. And the dynamic sports car test is used to verify the designed satellite navigation anti deception interference algorithm. The verification results show that when the satellite navigation is subjected to deception interference，the inertial/satellite integrated navigation switches to autonomous navigation，and the inertial navigation can continue to work with high accuracy. Compared with the traditional integrated navigation algorithms，the position accuracy is at least 6 times higher.This study can provide reference for the engineering implementation of satellite navigation anti deception interference in the design of inertial/satellite integrated navigation algorithms in the field of inertial navigation.

Function design of electronic chart display and information system-polar is studied based on the overall technology requirement of navigational charts in polar navigation. Firstly function requirements of ECDIS-Polar is analyzed based on the influence analysis of polar navigation environment and technology characteristics and demand analysis of project implementation. Then overall principles are presented and detailed function module architecture of ECDIS-Polar is constructed by borrowing general framework of conventional ECDIS. Lastly key technologies and solutions of ECDISPolar development are suggested. The research results provide a conceptual system design for ECDIS-Polar，which would be useful for the development and improvement of ECDIS-Polar.

When the horizontal attitude reference of celestial navigation equipment and the star tracker are installed separately，they are affected by the temperature change of the installation structure，stress release and other factors. The direct transmission of the horizontal attitude reference to the star tracker will introduce an installation error angle，which has a significant impact on the accuracy of celestial navigation. Aiming at the estimation problem of the installation error angle between the horizontal attitude reference and the star tracker，the installation error estimation model is design and derived，the measurement component is optimized，the relative motion strategy between the measurement component and the horizontal attitude reference is designed to determine the component and the horizontal attitude reference. The difference between the three-axis gyro data between the measured component and the horizontal attitude reference is used as the measurement information of the Kalman filtering，which can realize an effective estimation of the installation error. The simulation results show that a suitable model is designed，the angular velocity of the gyro is used as the measurement information of the Kalman filtering，and the stable state of the filter can be achieved in a short time through a certain rotation strategy，and the accuracy of horizontal installation error angle estimation is better than 3.6 arcseconds，and the accuracy of gyro bias estimation is better than 0.01 degrees per hour. Therefore，the algorithm has good adaptability for the transmission of the celestial navigation level attitude reference to the measurement component，and has practical value and research significance.

The star sensor is currently the most precise attitude measurement instrument. In the field of missile guidance，the star guidance technology utilizes the star sensor to correct the missile’s attitude error and improves the accuracy of the missile’s landing point. The high-precision missile guidance requires higher accuracy requirements for the star sensor’s measurement. The research status of high-precision star sensors at home and abroad is introduced in this paper. The error tree of the star sensor is given，the errors of the star sensor’s error tree are classified，and the sources of each error item in turn is analyzed. Finally，the methods to suppress the errors of the star sensor is proposed，including temperature compensation，filtering，inertial assistance，and optical zone calibration，with the aim of providing relevant ideas for the design of highprecision star sensors.

Compared with a single train positioning method，integrated navigation technology can effectively improve the performance of train positioning systems. This paper introduces the basic principle of the integrated navigation technology of strapdown inertial navigation system（SINS）/satellite navigation （GNSS） for trains，and proposes a practical Kalman filtering algorithm for loose integrated of inertial navigation and satellite navigation. By utilizing the technical advantages of inertial navigation and satellite navigation，it overcomes the adverse effects of geographical and environmental factors on train travel routes and continuously provides accurate positioning information for trains. By analyzing the actual travel data of complex routes，the accuracy of integrated navigation positioning meets the requirements. The practicability and effectiveness of the integrated navigation algorithm are verified，which ensures the safety of train operation and transportation efficiency.

Affected by the internal hardware facilities of the instrument and external disturbances，the clock group frequency difference data of the atomic clocks will have noise and coarse difference values，which seriously affect the stability and accuracy of the atomic clock signals. So an improved denoising algorithm for atomic clocks is proposed，that is the improved EMD-AKF algorithm. After the atomic clock data are removed from the coarse difference according to the 3σ criteria，the preprocessed data are analyzed by combining empirical mode decomposition and adaptive Kalman filtering. The dominant components in the IMF components after empirical mode decomposition are determined according to the Pearson's correlation coefficient and the autocorrelation coefficient. The noise-dominant IMF components are denoised by adaptive Kalman filtering，and the new atomic clock clock difference data are finally reconstructed. The stability assessment of the clock difference data before and after processing shows that the improved EMD-AKF algorithm improves the frequency stability of the atomic clock signal by one order of magnitude，and greatly reduces the influence of the noise of counters and other instruments on the frequency difference data of the atomic clock.

To meet both the requirements of optical pattern engineering and regulatory，and to quickly find the optimal pattern design and processing parameters，thereby resolving the need for extensive simulations and experiments to achieve multi-objective optimization from design to manufacturing，a comprehensive parameter optimization method based on sensitivity analysis is proposed in this paper. The results indicate that during the design phase，the optical pattern achieves optimal optical utilization performance when the surface roughness of the design parameters is maintained between 0.1 mm and 2 mm. During the manufacturing phase，using HP4A material as an example，the design is sampled using Latin hypercube sampling within the specified range of surface roughness，and the objective function is constructed based on its minimum value. The study examined the effects of cutting parameters：spindle speed（n），feed rate（Vf），and axial cutting depth（ap）on surface roughness（Ra），resulting in the identification of the optimal combination of cutting parameters.Through sensitivity analysis，it is shown that surface roughness negatively correlates with spindle speed and feed rate，and positively correlates with axial cutting depth. By using sensitivity analysis to quickly optimize the full parameters of optical patterns，the method reduces the number of design variables and improves solving efficiency by 30% compared to traditional experimental and simulation methods，which proves its effectiveness.

Zero value insulators threaten the safe and stable operation of transmission lines. Using the fiber optic electric field detection method，the local electric field distribution of insulator strings can be quickly detected，thereby identifying zero value insulator piece. A fiber optic electric field detection tracked robot is designed. To analyze the possible errors and impacts of fiber optic electric field detection robots during the detection process，an identification criteria is proposed. A true model of 220 kV insulator string and an equivalent model of fiber optic electric field detection robot are established. The electric field distribution characteristics of the robot architecture at different positions of the insulator string are simulated and analyzed. The influence of factors such as robot material，position，and size on the characteristics of local electric field distortion has been studied，especially the changes in local electric field under zero and non zero values. The research results reveal the influence of the fiber optic electric field detection robot on the local electric field distortion of zero value insulator，and thus provides technical support for the intelligent operation and maintenance of external insulation in power transmission and distribution.

In order to advance the green and low-carbon transformation of energy and establish a novel energy system，this paper proposes an innovative renewable energy system based on the combination of photovoltaic（PV）and passive optical network（xPON）technologies to promote the development of green electricity. Firstly，a system framework is constructed by interconnecting wind turbines and photovoltaic panels. Secondly，by integrating radio over fiber（RoF）and xPON networks，energy data is efficiently transmitted from wind turbines and solar panels to a central control station. Finally，an equivalent PV circuit and wind turbine model are established，and the efficient hybridization of wind and solar energy is achieved by combining convolutional kernel support vector machine with solar panels. Experimental results demonstrate that the system exhibits significant advantages with a scalability of 90% for PV modules，a service quality of 62%，low power consumption at 96%，high network efficiency at 92%，and a training accuracy of 95% in multiple aspects. Therefore，this research not only enhances the efficiency of renewable energy but also optimizes its performance in optical network environments，providing new possibilities for the integration of green energy and communication technologies.