Focusing on the underwater exploration potential of lidar and the limitations of physical limit on its detection sensitivity and detection accuracy, this paper focuses on modeling and analyzing the ultra-sensitive detection performance of entangled Fock state under seawater attenuation environment. Based on the LCMMS state, the entanglement detection model under seawater attenuation environment is established. The minimum phase error accuracy of LCMMS under the uniform distribution of photon number and the interference fringe contrast formula are derived. The simulation results show that the ultra-sensitive detection distance of the entangled Fock state under clear seawater can reach a distance of more than ten meters under water. The high photon number entangled state can make the distance higher; because LCMMS contains more high In the M and M' state of the photon number, the ultra-sensitive detection range of the quantum interferometric target detection of LCMMS under seawater loss is nearly 1.3 times that of the M and M' state.
The precise target identification is significant for commanding decisions and enemy identification. The micro-Doppler effect (MDE) can reflect the subtle movement characteristics of the target, which provides a new way for the target detection and recognition. However, the current research is mainly on the micro-motion feature extraction and classification of the targets, which is not capable for identifying the targets of the same type. This also reduced the application of the MDE. In fact, by accurately estimating the micro-motion parameters and combining sufficient prior knowledge, the target can be accurately identified. Further, the MDE detected by laser in infrared band has higher sensitivity and resolution than microwave detection, especially for the MDE generated by weak vibrations. Thus, in this paper, the photocurrent model of the laser detected MDE echo signal is established. The all-fiber coherent laser detection system for target micro-motion is designed. The detection sensitivity of and resolution requirements of the multicomponent micro-Doppler features are analyzed. Based on the time varying auto-regression (TVAR) model, the precise parameter estimation method for micro-motions are proposed, which provides the basis for target identification. The validity of the theoretical analysis and estimation method is verified through simulation. This research is helpful for extending the application of MDE from classification to precise identification in the future.
Coherent Doppler lidars (CDL) and coherent differential absorption lidars are widely applied in the measurements of atmospheric wind and constituents respectively. To improve the detection range of heterodyne lidars, the demands for laser linewidth are studied based on the statistical theory and Monte Carlo simulations. The signal to noise ratio (SNR) and the spectrum of intermediate frequency (IF) signal are analyzed under different laser power and linewidth. When the detection range is beyond the coherent length, the IF signal can still be measured, and the power spectrum of IF signal will be broadened, which results in the peak value decrease in the power spectrum. In heterodyne Doppler lidars, the frequency extraction errors of IF signal fluctuate with SNR. To realize the velocity measurement performance for wind and other moving targets, detection performances with various laser linewidth are analyzed according to the 3σ criterion. The calculations indicate that better results can be obtained with larger powers when the laser linewidth is relatively wider and that the effective detection range of lidar can be longer than the coherent length for lasers with certain linewidth. To verify the analysis, heterodyne experiments are carried out based on the fiber delay lines and fiber lasers with different linewidths, and the SNR is controlled by a variable optical attenuator. The results show that measurements with large laser power can reduce the errors caused by the power spectrum broadening of IF signal. The analysis may aid the determination of laser power and linewidth in heterodyne lidars.
With the increasing demands for new biological extinction materials in military and civilian fields, the artificially prepared flocculent biological particles are equivalent to bullet rosette particles. Then the unit particles with different numbers and lengths of branches are built, and the aggregated particles with different structures are built further. Next the structures of biological particles are characterized by parameterization. And the discrete dipole approximation method is used to calculate the extinction efficiency factor for biological particles. The results indicate that the structures and spatial arrangement of unit particles have great impact on the extinction performance of biological particles. The extinction performance of unit particles is positively correlated to the number and length of branches in the far infrared waveband. Furthermore, the extinction performance of aggregated particles is positively correlated to the porosity in the far infrared waveband. The model provides a theoretical basis for the further development and morphology control of biological extinction materials.
Laser reflective tomography(LRT) imaging is a effective technique in high-resolution imaging of remote target. Since the mass distribution information of target is contained in echo, the barycenter of target could be located from echoes in different angle. We proposed a universal method to locate the distance barycenter of 2D planar target or shelly target applied LRT. Simulation results show the barycenter could be located with relevant uncertainty of 0.0226.
The theoretical model and mathematical description of dual-balanced coherent detection ( or dual-balanced coherent detection ) are established，with which the current formula and output power formula of intermediate frequency (IF) signals are deduced. Theoretical analysis shows that this dual-balanced coherent detection technique can effectively solve the polarization matching of signal light and local light, and improve the stability of signal measurement, and reduce the influence on signal-to-noise ratio (SNR) of the system. Meanwhile, the technique also have the above advantages compared with single-balanced coherent detection. Hopefully, the dual-balanced coherent detection method could be applied in a wide range of fields.
Maximum Likelihood Estimation(MLE) is the optimal estimator for Micro-Doppler feature extracting. However, the enormous computational burden of the grid search and the existence of many local maxima of the respective highly nonlinear cost function are harmful for accurate estimation. A new method combining the Mean Likelihood Estimation(MELE) and the Monte Carlo(MC) way is proposed to solve this problem. A closed-form expression to evaluate the parameters which maximize the cost function is derived. Then the compressed likelihood function is designed to obtain the global maximum. Finally，the parameters are estimated by calculating the circular mean of the samples get from MC method. The high dependence of accurate initials and the computational complexity of the iteration algorithms are avoided in this method. Applied to the simulated and experimental data, the proposed method achieves similar performance as MLE but less computational amount. Meanwhile, this method guarantees the global convergence and joint parameter estimation.
As a novel imaging method, laser reflective tomography imaging can be used for long-range, high-resolution target imaging, with advantages that its spatial resolution is unrelated with the imaging distance, but related with laser pulse-width, bandwidth of detectors and noise. And it can also be easily realized in technology. The principle of range resolved laser reflective tomography imaging was firstly introduced in this paper. The experiment system of laser reflective tomography imaging was established and the projection data acquired by the experiment system was then analyzed and discussed. In the view of the quality of reconstructed image which used filtered back projection algorithm, the influences on reconstructed image quality that those factors such as filter type and projection data cause were compared, and the most critical factor that effect constructed image quality was found out. Experiment results showed that projection data quality is the key factor to reconstructed image quality in laser reflective tomography, Projection data reconstruction which means extracting target range-resolved data from laser echo was useful to improve reconstructed image quality.
In order to grasp the information of wind field and disturbance in the airport in real time, and to ensure the safety of flight, a method of detecting wind field disturbance using coherent laser is presented. A model to solve the vector velocity of the wind field disturbance is established in this paper. Based on the radial velocity simulation of coherent laser echo signal, a reliable and effective radial velocity data is provided for inversing the vector velocity of the wind field disturbance. Actually, the radial wind velocity appears relatively large fluctuations due to the distribution inhomogeneity of aerosol particles and sensor noise in actual measurement. Therefore, the purpose of adding random noise into the above-mentioned inversion of the radial wind velocity is to simulate the measured radial wind velocity data. In the case of noise interference, the damping least square algorithm is proposed to solve the numerical optimal vector velocity of the wind field disturbance to verify the solving model. In addition, the vector velocity of the wind field disturbance is compared and analyzed under different scanning azimuth interval. Through the simulation results, it shows that the mean square error(MSE) of inversion result is smaller with the decrease of scanning azimuth interval. When the scanning azimuth interval is less than 60°, the mean squared error of the vector velocity of the wind field disturbance is less than 1.14m/s, horizontal direction disturbance quantity is less than 4°, which lays a good theoretical basis for the follow-up field tests.
Quantum Sensors like Quantum Radar and Lidar based on the interference of non-classical states can achieve super-sensitivity beyond the Standard Quantum Limit (SQL). But as the photons transporting in atmosphere, the environmental interaction causes quantum de-coherence and results in the reduction of super-sensitivity range of the quantum sensors. The most significant effect of atmospheric transmission is photon loss along with phase fluctuation. In this letter, we introduce both the photon loss and phase fluctuation by adding a fictitious beam splitter in the signal arm of Mach- Zehnder interferometer (MZI). The density matrix with N00N and M&M' entangled states being the input states under the condition of photon loss and phase fluctuation is given respectively. Then as the optimal detection schemes parity operator is used as the detector and the formula of the sensitivity is derived. The super-sensitivity range of M&M’ and N00N states with de-coherence are simulated. As a consequence, with high photon loss M&M’ states shows the better phase sensitivity than N00N states but the N00N state is better when the loss is smaller than 20%. And with pure phase fluctuations N00N states get the longer range. M&M’ states is sensitive to the transmittance difference between two arms of the interferometer.