With the maturity of LiDAR technology, LiDAR point cloud segmentation has been widely applied in automatic inspection of power lines. However, in weather scenarios such as rain, snow, and dust, lidar data noise and dynamically changing power line data can be generated, resulting in a decrease in power line extraction efficiency. The commonly used airborne LiDAR can only work in sunny weather conditions, and in order to improve the accuracy of point cloud power line extraction, the data collected on board needs to be preprocessed to obtain complete scene point cloud data, which cannot meet the requirement of automatic inspection of power lines.In order to solve the problems of real-time monitoring of airborne LiDAR data and low accuracy in extracting power line point clouds under different weather scenarios, this paper proposes a point cloud power line extraction method based on the improved DBSCAN algorithm, starting from the data features of fixed LiDAR real-time scanning point clouds. Firstly, the cloth filtering method is used to filter out ground points and obtain non ground point clouds; On this basis, based on the spatial relative density characteristics of non-ground point clouds, target data such as traverse points and tower points are roughly extracted from non-ground points; Then, the distribution characteristics of the elevation point cloud are used to identify the tower, and the maximum width of the tower is used to segment the power lines within the range of the tower. Then, based on the data characteristics of the point cloud, the density clustering parameters are continuously modified to further improve the accuracy of power line point cloud segmentation. In order to verify the effectiveness of the algorithm, point cloud power line point cloud segmentation experiments were conducted in different meteorological environments, and compared with European clustering segmentation and regional growth algorithms. The experimental results show that the improved DBSCAN algorithm proposed in this paper has the best segmentation performance for power line point clouds in complex weather scenarios, which is basically consistent with sunny conditions and can meet the actual power inspection needs.
When detecting moving targets via photon counting Lidar, the target information contained in the echo photon statistical histogram is distorted, because the target position in a cumulative time changes. To solve the above distortion, this work proposed a method of acquiring moving target structural characteristics from the photon echo statistical histogram via waveform processing. Firstly, the probability distribution model of photon detection echo corresponding to a moving target was established. Then, the mathematical expressions of the laser radar cross section (LRCS) and depth structure corresponding to a moving target were derived by utilizing the photon waveform correction and waveform fitting filtering. Finally, the structural characteristics of a multi-layer moving target with a speed of 20m/s at 10km were obtained. Under the condition of SNR (signal-to-noise ratio) being 1.48, to detect a multi-layer moving target composed of two sub-targets with 0.5×1m, between which the distance was 0.5m, when the detection time was 0.01s (i.e., the cumulative number was 300), the consequential LRCS was 1.009m², and the ratio of LRCS within the moving target was 0.967:1. Meanwhile, the depth within the sub-targets was 0.493m, whose error was less than 0.7%. The proposed method in this work provided theoretical support for the acquisition of moving target detail information and the recognition of moving targets.
Rough target can cause the wavefront distortion of laser return, which shows the decoherence phenomenon and reduces the detection performance of heterodyne lidar systems. In fact, the decoherece process includes both the laser source and the rough target. The actual laser beams are usually partially coherent, and the atmospheric turbulence aggravates the coherence of laser spots on the rough target and the backscattered laser return. The backscattered laser field of rough plane is derived based on the GSM beam and the generalized Huygens-Fresnel principle. And the beam truncation effect of actual optical transceiver is also analyzed by using the hard edge aperture function. The laser return intensity variations are obtained by considering the laser beam coherence, the rough surface height fluctuation and the atmospheric turbulence. Then decoherence effects are calculated via the complex coherence degree under typical roughness parameters and laser wavelengths. For practical target, the complex coherence degree can be approximated by the Dirac delta function, and then the system efficiency and the effective coherent solid angle can also be used for further analyses. The results show a positive correlation between the decoherence effect and the roughness. The research on the scattering characteristics of rough planes expands the scattering theory and provides a reference for the design and analysis of long-range and high-precision heterodyne lidar system.
For detecting long-distance moving aerial targets, in order to solve the problem of low accumulation times and weak echo signal, this work proposes a multi-beam staring photon detection method. Firstly, the photon waveform expression of multi-beam staring photon detection is deduced. Then, the relationships between divergence angle, pulse width, single pulse energy, laser repetition frequency and photon probability distortion are discussed. Finally, the method of calculating the system transmitter parameters is obtained. The results show that when the detection target is the F22 flight with a speed of 400m/s at a distance of 10km, the number of beams is set to 40, the launch angle is set to 2mrad, the pulse width is set to 1ns, and the single pulse energy is set to 0.5μJ at the transmitting end. The research results provide a theoretical basis for the system design and realization of long-distance and fast-moving aerial targets.
KEYWORDS: Signal to noise ratio, Heterodyning, LIDAR, Signal detection, Polarization, Fiber lasers, Pulsed laser operation, Digital signal processing, Monte Carlo methods, Sensors
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.
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.
Laser reflective tomography is a long-range, high-resolution active detection technology, whose advantage is that the spatial resolution is unrelated with the imaging distance. Accompany satellite is a specific satellite around the target spacecraft with encircling movement. When using the accompany satellite to detect the target aircraft, multi-angle echo data can be obtained with the application of reflective tomography imaging. The feasibility of such detection working mode was studied in this article. Accompany orbit model was established with horizontal circular fleet and the parameters of accompany flight was defined. The simulation of satellite-to-satellite reflective tomography imaging with satellite-accompany was carried out. The operating mode of reflective tomographic data acquisition from monostatic laser radar was discussed and designed. The flight period, which equals to the all direction received data consuming time, is one of the important accompany flight parameters. The azimuth angle determines the plane of image formation while the elevation angle determines the projection direction. Both of the azimuth and elevation angles guide the satellite attitude stability controller in order to point the laser radar spot on the target. The influences of distance between accompany satellite and target satellite on tomographic imaging consuming time was analyzed. The influences of flight period, azimuth angle and elevation angle on tomographic imaging were analyzed as well. Simulation results showed that the satellite-accompany laser reflective tomography is a feasible and effective method to the satellite-to-satellite detection.
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.
This paper consults and improves the on hand computational methods and circuits, which comprehensively utilizes the
knowledge of the Aerodynamics, the heat transfer theory, the radio optics, ANSYS and so on. In the analysis of the IR
characteristics of aerial targets, taking it into account that most of the computing methods on hand are empirical or
semi-empirical, which are more simple, but more limited, less sufficient and scientific and have more human factors, so
we begin with the determination of the thermal field, adopt the numerical method to realize the calculation and modeling
of the IR radiation with ANSYS, analysis how the spectral coverage and the observed bearing affect the IR radiation, and
then get the credible and all-side numerical calculation results.
Then, this paper introduces a method utilizing 3DS MAX and OpenGL to generate the IR picture of the target,
which divides the grey level of the IR radiation reasonably according to the final numeric calculating results and
the principle of the grey level division, and then we generate the IR pictures of the aerial targets.
The CO2 differential absorption lidar (DIAL) technique have advantages such as high vertical and horizontal resolution,
the ability to acquire simultaneous species and aerosol profiles, day and night coverage and no dependence on external
radiation. An all solid-state l.5 μm CO2 differential absorption coherent lidar was designed in the paper. The key
technology of the system such as high precision laser wavelength control, echo correlation detection were solved the
tunable-diode-laser (newfocus model 6330) was selected as the laser source. The reference CO2 gas pool was selected as
for absorption calibration. The modulated laser signal was sent through the gas pool and detected by the detector. By
observing the frequency of output voltage of the detector, the wavelength of the on-laser was locked. The experiment
showed the precision of the laser wavelength control was under 0.1pm which is narrower than the CO2 absorption band
width. The aim of the echo coherent detection is promoting the SNR of the Lidar. By the polarization separating and
collecting for the echo and local-oscillator signal, the problem of polarization matching between the echo and seed was
solved. The balanced detector was selected to achieve the balanced detection, which remarkably eliminated the affection
of the local-oscillator noise. The laboratorial experiment for the lidar was carried out to detect the CO2 inside the gas
pool. The analysis of the experiment data showed the CO2 detection sensitivity of the system is up to the 25ppm pre
kilometer long path.
The product surface roughness measurement occupies an important position in the manufacturing process of the
industrial product. The laser speckle image can be used for the non-contacted measurement. The Speckle images are
produced by the reflected and scattered light beams from rough surface through free-space to observing plane when laser
illuminates the object surface. Statistical distribution of speckles depends on the microscopic structure of the rough
surface and can be used to distinguish the surface roughness. Firstly, for the existence of the noise and redundancy in the
laser speckle image, the PCA(principal component analysis) method is utilized in the image processing. After extracting
the principal components in the original image matrix, the reconstruction image which removed noises and irrelevances
was earned. Secondly, the fractal features of reconstruction images were extracted by using the Double Blanket Method.
The fractal dimension of the reconstruction image was analyzed under the moving window with optimum size to obtain
the fractal dimension histogram. By comparing the histogram with the surface roughness, the obvious correlations of the
frequency point distributing of the fractal dimension histogram and the product surface roughness was shown. On these
bases, the multi-scale fractal features were extracted for the single-scales limitation. So, the method of product surface
roughness measurement based on the fractal feature of the laser speckle image was given by the research. The measure
system set-up of the method is simple, fast, and not sensitive to change of circumstance and vibration. Hence, it has great
potential for application to in-process measurement.
Airfoil trailing vortex is an important reason for the crash, and vortex detection is the basic premise for the civil
aeronautics boards to make the flight measures and protect civil aviation's security. So a new method of aircraft trailing
vortex detection based on laser's multiplex information echo has been proposed in this paper. According to the classical
aerodynamics theories, the formation mechanism of the trailing vortex from the airfoil wingtip has been analyzed, and
the vortex model of Boeing 737 in the taking-off phase has also been established on the FLUENT software platform.
Combining with the unique morphological structure characteristics of trailing vortex, we have discussed the vortex's
possible impact on the frequency, amplitude and phase information of laser echo, and expounded the principle of
detecting vortex based on fusing this information variation of laser echo. In order to prove the feasibility of this detecting
technique, the field experiment of detecting the vortex of civil Boeing 737 by laser has been carried on. The experimental
result has shown that the aircraft vortex could be found really in the laser scanning area, and its diffusion characteristic
has been very similar to the previous simulation result. Therefore, this vortex detection means based on laser's multiplex
information echo was proved to be practicable relatively in this paper. It will provide the detection and identification of
aircraft's trailing vortex a new way, and have massive research value and extensive application prospect as well.
The improving resolving power of laser imaging system is limited by the laser footprint size on the target. Employing
only echo delay and intensity information, the information of the targets inside the footprint is difficult to be obtained for
the echo signal of the targets maybe is submerged by each other. Under the remote laser imaging, the serious loss of
image quality may occur because of the large footprint. The target detection method based on the single laser return
waveform was studied and the provided to get the target information inside the laser footprint. Firstly, the basis laser
echo signal model of the target inside the footprint was built. On the basis, the decomposition algorithm was provided
which can decompose a laser return waveform into a series of components assuming that each component corresponding
to a sub-target inside the laser footprint. After the primary sub-target return waveforms was obtained, however, there still
exists some small sub-targets inside the laser footprint whose return signal is hardly to be extracted because they are
submerged by the neighborhood sub-target return signal. The subtracting algorithm between the whole return waveform
and the components waveform provides the way to get the submerged return waveforms of sub-target. So, the
information of sub-targets inside the laser footprint would be obtained. In the end, the actual laser return data was
analyzed employing the method to get the range position information of the sub-targets inside the laser footprint, which
verifies the method validity.
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