Streak Tube Imaging Lidar Research Articles

Design and Validation of a Long-Range Streak-Tube Imaging Lidar System with High Ranging Accuracy

The Streak-Tube Imaging Lidar (STIL) has been widely used in high-precision measurement systems due to its ability to capture detailed spatial and temporal information. In this paper, we proposed a ranging measurement method that integrates a Time-to-Digital Converter (TDC) with a streak camera in a remote STIL system. In this method, the TDC accurately measures the trigger pulse time, while the streak camera captures high time-resolution images of the laser echo, thereby enhancing both measurement accuracy and range. A corresponding ranging model is developed for this method. To validate the system’s performance, an outdoor experiment covering a distance of up to 6 km was conducted. The results demonstrate that the system achieved a distance measurement accuracy of 0.1 m, highlighting its effectiveness in long-range applications. The experiment further confirms that the combination of STIL and TDC significantly enhances accuracy and range, making it suitable for various long-range, high-precision measurement tasks.

High Accuracy Reconstruction of Airborne Streak Tube Imaging LiDAR Using Particle Swarm Optimization

Airborne streak tube imaging LiDAR (STIL) consists of several different data-generating subsystems and introduces system errors each time it is installed on an aircraft. These errors change with each installation, which makes the parametric calibration of the LiDAR meaningless. In this study, we propose a high-precision reconstruction method for point clouds that can be used without calibrating the system parameters. In essence, after each remote sensing measurement, a self-checking process is performed with experimental data to replace the fixed system parameters. In this process, the splicing error of the same region measured under different conditions is used as a criterion to optimize the reconstruction parameters via a particle swarm optimization (PSO) algorithm. For a detection distance of 3000 m, the elevation error of the point cloud reconstruction reaches more than 1 m if the placement parameters are not optimized; after optimization, the elevation error can be controlled within 0.3 m.

Streak tube imaging lidar with kilohertz laser pulses and few-photons detection capability

Lidar using active light illumination is capable of capturing depth and reflectivity information of target scenes. Among various technologies, streak tube imaging lidar (STIL) has garnered significant attention due to its high resolution and excellent precision. The echo signals of a STIL system using single laser pulse are often overwhelmed by noise in complex environments, making it difficult to discern the range of the target. By combining high-frequency laser pulses with the repetitive sweep circuit, the STIL system enables efficient detection of few-photons signal in weak-light environments. Additionally, we have developed a robust algorithm for estimating the depth and reflectivity images of targets. The results demonstrate that this lidar system achieves a depth resolution better than 0.5 mm and a ranging accuracy of 95 um. Furthermore, the imaging of natural scenes also validates the exceptional 3D imaging capability of this system.

Pre-segmentation of point cloud based on centroid matrix of streak tube imaging LiDAR

Pre-segmentation of point cloud based on centroid matrix of streak tube imaging LiDAR

A Calibration Method for Time Dimension and Space Dimension of Streak Tube Imaging Lidar

Owing to the special working systems of streak tube imaging lidar (STIL), the time and space dimensions are coupled together on the streak images. This coupling can cause measurement errors in 3D point clouds and can make measurement results more complicated to calibrate than other kinds of lidars. This paper presents a method to generate a time calibration array and an angle calibration array to separate the offset of the streak into time dimension and space dimension. The time and space information of the signal at any position on the streak image can be indexed through these two arrays. A validation experiment on aircraft was carried out, and the range error of the 3D point cloud was improved from 0.41 m to 0.27 m using the proposed calibration method. Thus, using the proposed calibration method can improve the accuracy of the point cloud produced by STIL.

3-D Imaging Lidar Based on Miniaturized Streak Tube

Abstract Streak Tube Imaging Lidar (STIL), with advantages of non-scanning working mode, small distortion, high image framing rate, high resolution in low contrast environment, compact structure, easy miniaturization and high reliability, has a wide range of applications in military, aerospace, space confrontation, attack and defense, and marine law enforcement. This article introduces the principle of single-slit and multi-slit streak tube imaging lidar. It also introduces a single-slit general streak camera that can be used for imaging lidar. In addition, a multi-slit miniaturized streak tube with a single-lens focusing system with a total length of about 200 mm has been designed. The results of the 3D electromagnetic simulation show that the effective photocathode area of this streak tube reaches 36 mm × 36 mm, the temporal resolution is better than 50 ps, the dynamic spatial resolution can reach 12 lp/mm, and the whole photocathode can accommodate at least 19 slits in the effective detection range. The streak tube has a meshless structure, which is highly reliable. The streak tube can be used to increase the field of view of the imaging lidar system, improve the reliability, and achieve system miniaturization.

Airborne Streak Tube Imaging LiDAR Processing System: A Single Echo Fast Target Extraction Implementation

In this paper, a ground target extraction system for a novel LiDAR, airborne streak tube imaging LiDAR (ASTIL), is proposed. This system depends on only a single echo and a single data source, and can achieve fast ground target extraction. This system consists of two modules: Autofocus SSD (Single Shot MultiBox Detector) and post-processing. The Autofocus SSD proposed in this paper is used for object detection in the ASTIL echo signal, and its prediction speed exceeds that of the original SSD by a factor of three. In the post-processing module, we describe in detail how the echoes are processed into point clouds. The system was tested on a test set, and it can be seen from a visual perspective that satisfactory results were obtained for the extraction of buildings and trees. The system mAPIoU=0.5 is 0.812, and the FPS is greater than 34. The results prove that this ASTIL processing system can achieve fast ground target extraction based on a single echo and a single data source.

Development of a large-field streak tube for underwater imaging lidar.

Streak tube imaging lidar (STIL) can obtain 4-D images of a target, and its performance is mainly determined by the streak tube sensor. To obtain a large field of view, we developed a streak tube with a photocathode length as large as 35.3 mm, which is larger than the commonly used ST-HDR (30 mm). At the same time, the temporal resolution and dynamic spatial resolution are 60 ps and 12 lp/mm, which are very suitable to obtain accurate target coordinates for 4-D imaging. In addition, the streak tube has a high detection sensitivity of 46 mA/W at 500 nm and, hence, prospects in remote imaging. To test the performance of the streak tube, an underwater STIL experiment was conducted. Echo signal processing was performed by means of a bandpass filter and a matched filter, and then the peak detection algorithm was used to reconstruct the image. The results indicate that a spatial resolution better than 9 mm is achieved in the limpid water with a depth of 20 m, and a range accuracy of 1 cm is achieved in the turbid water with a depth of 10 m. Such a performance suggests that the large-field streak tube is of great potential for underwater target imaging and other remote imaging applications.

Extracting suburban residential building zone from airborne streak tube imaging LiDAR data

In this paper, we proposed a novel method for extracting suburban residential building zone (SRBZ) from airborne streak tube imaging LiDAR (STIL) data. This method is implemented using a single data source, which avoids the collections of multi-source data and shortens the production cycle of LiDAR data products. The framework of the method is mainly composed of a prediction module, and a correction module. In the correction module, two correction algorithms were proposed, that is, k-nearest neighbor majority voting correction algorithm (k-NNMV) and Gaussian weight based k-nearest neighbor voting correction algorithm (GWk-NNV). Experiment tests show that the framework based on the GWk-NNV has a better SRBZ extraction effect than that of the k-NNMV. The F1 coefficient of the GWk-NNV-based framework reached 80.10%. That proves that the proposed method for extracting SRBZ from airborne STIL data is feasible.

Theoretical and Experimental Research on Spatial Performances of the Long-slit Streak Tube

Abstract The streak tubes are widely used in National Ignition Facility (NIF), Inertial Confinement Fusion (ICF), and streak tube imaging lidar (STIL) as radiation or imaging detectors. The spatial resolution and effective photocathode area of the streak tube are strongly dependent on its operating and geometry parameters (electron optical structure and applied voltage). Studies about this dependence do not cover the full range of the parameters. In this paper, 3-D models are developed in Computer Simulation Technology Particle Studio (CST-PS) to comprehensively calculate the spatial resolution for various parameters. Monte Carlo Sampling method (M-C method) and spatial modulation transfer function method (SMTF) are employed in our simulation. Simulated results of the optimized spatial resolution are validated by the experimental data. Finally, the radii of the photocathode (R c) and phosphor screen (R s) are optimized. Geometry parameters of R c=60 mm and R s=80 mm are proposed to optimize the streak tube performances. Simulation and experimental results show that the spatial resolution and effective photocathode area of this streak tube are expected to reach 16 lp/mm and 30 mm-length while the voltage between cathode and grid (U cg) is 150 V.

Denoising of the multi-slit streak tube imaging LiDAR system using a faster non-local mean method.

Combined with the characteristic of the multi-slit streak tube imaging LiDAR (MS-STIL) system where the imaging areas corresponding to each slit do not interfere with each other, we denoised the streak images by an improved fast non-local mean filtering algorithm. Experiments were performed to investigate the effectiveness of the method. The experimental results show that the spatial resolution of the system is improved from 22 to 16 mm; the relative distance error is reduced by an average of 22.76%; and the intensity accuracy improved significantly when the distance is 10 m. Additionally, the overall denoising effect is comprehensively verified by long-range target imaging. The mean square error of the reconstructed depth image and intensity image are reduced from 0.0836, 0.0067 to 0.0433, 0.0037, respectively. The applicability of the proposed method was verified through comparative experiments in different environments.

Target classification of multislit streak tube imaging lidar based on deep learning.

To reduce the impact of the image reconstruction process and improve the identification efficiency of the multislit streak tube imaging lidar (MS-STIL) system, an object classification method based on the echo of the MS-STIL system is proposed. A streak image data set is constructed that contains a total of 240 common outdoor targets in 6 categories. Additionally, the deep-learning network model based on ResNet is chosen to implement streak image classification. The effects of two classification methods based on streak images and reconstructed depth images are compared. To verify the maximum classification capability of the proposed method, the recognition effects are investigated under 6 and 20 classes. The results show that the classification accuracy decreases from 99.42% to 67.64%. After the data set is expanded, the classification accuracy improved to 85.35% when the class number of the target is 20.

Design and modeling of multi-spectral polarimetry streak tube imaging LiDAR

A new Multi-Spectral Polarimetry Streak Tube Imaging LiDAR (MSP-STIL) system is proposed, with mathematical model of the system established and verified. Multiple experiments are conducted before drawing conclusions. Intensity images and degree of polarization (DOP) images at three wavelengths and a depth image of the target area can be obtained by the single imaging mode of the system, and Mueller matrices at three wavelengths of the target area can be obtained by the twice imaging mode of the system. Meanwhile, the proposed system utilizes the fiber optic delay device to alleviate the contradiction of traditional streak tube imaging LiDAR system among the large number of echo signals, the depth resolution and the depth of field. Therefore, the proposed system can perform multi-spectral polarimetry imaging and three-dimensional imaging with higher depth resolution and larger depth of field. Compared with the traditional single-wavelength streak tube imaging LiDAR system, the image contrast of the target area can be improved by fusing the spectral information, polarization information and three-dimensional information obtained by the proposed system, and the high-contrast image makes it easier to distinguish the target.

Occluded target detection of streak tube imaging lidar using image inpainting

We improve the system of multi-slit streak tube imaging lidar (MS-STIL) for occluded target detection. To solve the contradiction between high range resolution and deep depth of field, a fiber-optic beam, called ‘beam shunting’, is designed. In addition, we combine the deep-learning-based image inpainting algorithm with the MS-STIL to solve the problem of ineffective imaging when the target is obscured by a large area. Finally, the results of the simulated contrast experiments show that the range resolution is increased from 0.4 m to 0.1 m, and the new system is effective in detecting occluded targets.

Ground target extraction using airborne streak tube imaging LiDAR

Airborne LiDAR has become a kind of indispensable measurement device in the current field of remote sensing. However, target extraction using traditional airborne LiDAR based on single-point scanning requires filtering and point cloud segmentation operations, which are complicated and time consuming. Although some researchers have studied streak tube imaging LiDAR (STIL) before, there are few reports in which it is used as an airborne LiDAR for ground measurement in large-scale field. We propose a method of ground target extraction using STIL. Taking advantage of the structural properties of the STIL, complex filtering and point cloud segmentation algorithms are avoided in the target extraction method. The purpose of this article is to verify the feasibility of airborne STIL in ground target extraction. We analyzed the raw streak signal image collected by field experiment and used morphology and intensity information to extract features. After that, we employed the decision tree classifier to classify the four kinds of targets and evaluated the extraction results. The results show that the target extraction achieved satisfactory consequences under an acceptable level. That demonstrates that ground target extraction using STIL is feasible in the field of large-scale remote sensing.

Differential optical-path approach to improving the performance of Multiple-Slit Streak Tube Imaging LiDAR

A new Multiple-Slit Streak Tube Imaging LiDAR (MS-STIL) system based on differential optical path is proposed, with mathematical model of this system established and verified. Multiple simulations are conducted before drawing the conclusions. Determining the position of the low sensitivity peak point of traditional streak spot in the traditional system is converted to determining the position of a high sensitivity zero-crossing line of differential streak spot in the proposed system, where the optimal sensitivity of zero-crossing line can be obtained by adjusting the differential length of optical path and the sweeping speed of streak tube. The background noise is effectively suppressed in the proposed system, with higher signal-to-noise ratio (SNR) of the proposed system at same distance detection. The improvements above render higher three-dimensional imaging accuracy of the proposed system than the traditional system.

Comparison of four deblurring methods for streak image of streak tube imaging lidar

In this study, the Richardson–Lucy (R–L) iteration, Tikhonov (T–K) regularization, and fast iterative shrinkage-thresholding algorithm (FISTA) are first used to deblur streak images. The deblur performances of these three methods are compared with that of Wiener deconvolution. The spatial resolutions of Wiener deconvolution, R–L iteration, T–K regularization, and FISTA improved from 9 mm to 4.5, 5, 5, and 5 mm, respectively. The root-mean-square errors (RMSE) of one -, two -, and three-plane targets decreased effectively using these three deblur methods. The R–L iteration performs the best in terms of the RMSE for the two-plane target. The effects of the parameters used in each method are investigated.

High energy LiDAR source for long distance, high resolution range imaging

AbstractHigh energy, high repetition rates laser with excellent beam quality are fundamental components for LiDAR. In particular, high pulse energy is benefit for long distance range imaging. Narrow pulse width and high repetition rates are benefit for high resolution and high refresh rate operation of LiDAR. However, increasing the laser repetition rates will cause the pulse energy decreasing and the pulse width expanding. In order to achieve the requirements at the same time, we propose a 885 nm laser diode end‐pumped RTP Q‐switched Nd:YAG laser. Pulse pumping scheme was used to avoid heat accumulation. With a master oscillator power amplifier (MOPA) system, 40.5 mJ, 7.5 ns of 1064 nm pulses were obtained at 2 kHz. The beam quality factor M2 was measured as 1.60/1.51. Moreover, by frequency doubling with a LBO crystal, 16.4 mJ, 6.5 ns of 532 nm laser with the M2 factor of 1.52 and 1.50 was obtained. The 1064 and 532 nm pulses are suitable for avalanche photodiode arrays LiDAR and streak tube imaging LiDAR, respectively. The laser system is shown to accomplish high stability from temperature of −10°C to 30°C and vibration frequency of 10 to 100 Hz.

Deblurring streak image of streak tube imaging lidar using Wiener deconvolution filter.

We use a Wiener deconvolution filter to deblur the streak image of streak tube imaging lidar to improve the spatial resolution of the system and reduce the edge blurring effect in point clouds. Experiments were performed to investigate the performance of the deconvolution method. Results show that the spatial resolution improved from 9 to 4.5 mm, and the root-mean-square errors of the edge regions are effectively reduced. Additionally, the transition section decreases from 14 to 5.6 mm when the target is 5 m away from the receiver.

Design of precise delay system for streak tube imaging lidar

A precise delay system for a streak tube imaging lidar (STIL) is developed. Two delay schemes are designed that are suitable for long- and short-distance lidar imaging. The digital scheme delay can reach 100 μs, and its precision is <6 ns; the analog scheme delay can reach 1200 ns and its precision is <1 ns. Using the STIL system, three-dimensional (3-D) imaging experiments are carried out on land targets at about 2.3-km range and underwater targets at about 25-m range. The experimental results show that the designed delay device can produce precise delay times and effectively verify the 3-D imaging quality of the STIL. This device also has the advantages of stable operation, being more compact, and requiring less power than existing instruments.