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.
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.
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.
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.