Geiger-mode Avalanche Photodiodes Research Articles

Repeated γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma $$\\end{document} irradiation and thermal annealing via built-in thermo-electric coolers of Si avalanche photodiodes

When operating in space, on-board Silicon Geiger-Mode Avalanche Photodiodes (GM-APDs) are exposed to radiation damage that result in an increase in dark count rates. Thermal annealing has been found to mitigate the damage, although prior studies have largely focused on annealing following a single session of proton irradiation. This work reports that thermal annealing can be performed simply with the built-in thermo-electric coolers of the GM-APDs. Annealing was also done in 10 min intervals for a clearer view of the recovery curve. Mitigation of damage from repeated γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma $$\\end{document} radiation was observed from the: (1) halving of the increase in dark count rates on average and (2) outperformance of room temperature annealing (25∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$25\\,^{\\circ }$$\\end{document}C) by 33%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document}. Additionally, we show that heavy doses of γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma $$\\end{document} radiation (21 krad) have a probability of causing Random Telegraph Signals in GM-APDs that can be suppressed by lowering the operating temperature.

A novel GM-APD array-based heterodyne imaging detection system supports large array multi-pixel parallel target motion state image detection

Existing laser active imaging detection methods are limited by the detection mechanism, which can only capture the intensity image and distance image of the target, and lack practical detection solutions for acquiring images of the target motion state characteristics (non-macroscopic centroid motion, such as rotation, rolling, and other motion characteristics around the centroid). In this paper, a detection method using Geiger mode avalanche photodiode (GM-APD) array detector for heterodyne imaging to obtain images of the target motion state is proposed. An innovative method based on photon counting time interval calculation (PCTIC) is proposed to obtain the Doppler frequency shift of the target echo for each GM-APD pixel, which effectively eliminates useless data unrelated to the signal. With limited data storage and processing speed, the heterodyne imaging performance has been effectively improved to achieve high-precision heterodyne imaging detection of very weak target echoes and to support heterodyne imaging detection of large arrays with more image pixels in parallel. Experiments show that the method can achieve video-level detection at an imaging resolution of 32×32, and with a paucity of echo photons (detection probability of echo is 0.0032), a millimetre-level velocimetry measurement error can be achieved by accumulating only 6 echo photons per image element. The system also shows good resistance to turbulence interference, with target motion state characteristics detected based on velocity images remaining virtually unaffected under turbulence conditions caused by strong flames. This advancement is crucial for target detection in complex working environments such as smart manufacturing and autonomous driving.

Enhancing large-area Geiger-mode avalanche photodiode performance through dynamic memristor quenching: a study on improving count rate, reducing jitter and mitigating afterpulsing

While the larger photosensitive area of Geiger-mode avalanche photodiodes (GmAPDs) enhances their detection range and signal collection, improving their utility in weak light detection, their practicality is limited by a long recovery time, high afterpulsing probability (AP) and excessive jitter. Utilizing a dynamic memristor as a quenching resistor, this research improves the count rate of a large-size GmAPD by 100× at an overvoltage of 2.5 V, compared with a fixed resistor-quenched GmAPD. Furthermore, at a photon pulse frequency of 1 MHz jitter time is reduced from 3.60 ns to 0.48 ns, and the afterpulsing probability is effectively mitigated from 30.88% to 8.58%.

COA: A novel contrast fusion algorithm for GM-APD range image and infrared image under low-photon condition

Most existing image fusion methods focus on infrared images and visible images, which underperform under complex conditions. However, they cannot effectively distinguish similar targets at near distances and it limits the target recognition, especially when the image is missing badly under low photon conditions. To solve this problem, we propose a contrast optimization algorithm (COA) for fusing the Geiger-mode avalanche photodiode (GM-APD) image and infrared image that could emphasize and distinguish similar targets in low photon conditions. The COA method includes two main parts. First, using the processed infrared image as a reference to recover the GM-APD image by using DLatLRR system methods and reference recovery method. Then, we proposed a new loss function consist of contrast fidelity term and regularization term which focus on the contrasts of the infrared image and GM-APD image, and introducing the split Bregman to solve the optimization equation. Results show that the value of contrasts between targets (TC) of the proposed method is twenty times more than the infrared image and higher than that of the other 9 fusion algorithms when the mean photon per pixel (PPP) is 1/500. Meanwhile, the proposed method can also be used for combined with the existing fusion methods to fuse the infrared image and GM-APD image, which makes accurate target identification under low photon conditions.

Reconstruction algorithm of Gm-APD LiDAR based on synchronized pseudo-random time coding

Efficient photon counting imaging of long-range targets is challenging, especially in low signal-to-back ratio (SBR) situations. In this paper, a synchronized pseudo-random time coding detection method for Geiger-mode avalanche photodiode (Gm-APD) light detection and ranging (LiDAR) is proposed, which realizes Gm-APD LiDAR long-range detection by combining pseudo-random time coding and time of flight, and the multiple peaks are used to de-noise the image at the image level. Scenes of building with different SBR are simulated with Monte Carlo methods, and the effect of coding length on algorithm performance is discussed and compared with the performance of non-coding algorithms. The high performance of the proposed algorithm is verified by field experiments in low SBR scenes. Moreover, the proposed algorithm improves the target reconstruction correctness ratio by 70% over the other non-coding algorithms to 83% in the scene of building with SBR of 0.015, and has the smallest root mean square error (RMSE) of the distance. It improves the target integrity and provides the possibility of practical application of LiDAR target detection in very low SBR and long-range conditions, and even more support for target feature extraction and target recognition.

X-ray timing detectors with HfO2 nanoparticle-loaded plastic scintillator and silicon avalanche photodiode

We successfully developed 20- and 40-wt% HfO2-nanoparticle-loaded plastic scintillators (Hf-PLSs), and subsequently, assembled X-ray timing scintillation detectors using the Hf-PLSs and silicon avalanche photodiodes (Si-APDs) as the photodetector. Two types of Si-APDs were examined for two different detectors. A proportional-mode APD (pAPD) exhibited a nanosecond response, but a relatively low internal gain of less than several hundred. By contrast, a Geiger-mode APD exhibited a high gain of 105−6, but its output pulse width was longer than several tens of nanoseconds; the pixelated device is called as SiPM. A pAPD (Hamamatsu Photonics S8664-4433, 3 mm in diameter) was used as the photodetector and was combined with 20 wt% Hf-PLS (∼3 mm cube) as the X-ray scintillation timing detector. A SiPM (Hamamatsu Photonics S13360-3025, 3 mm × 3 mm) was assembled with 40 wt% Hf-PLS (∼3 mm cube). The characteristics of the two types of scintillation timing detectors were evaluated using a 57.61-keV synchrotron X-ray beam to assess their applicability in nuclear resonant scattering experiments. Both the detectors were cooled down to −35 or −20 °C to reduce noise and obtain a higher APD gain. A good time resolution of (0.31 ± 0.04) ns (FWHM) was easily obtained with the SiPM detector using a large APD gain at −20 °C, although the time resolution of the pAPD detector finally reached (0.39 ± 0.04) ns (FWHM) at −35 °C owing to a small gain of 146. However, a maximum count rate of over 1.4 × 107 s−1 was observed owing to the fast response of the pAPD detector, whereas the SiPM detector exhibited a maximum count rate of 5.9 × 106 s−1 because of the long pulse tail of ∼30 ns.

Fractional-Order Total Variation Geiger-Mode Avalanche Photodiode Lidar Range-Image Denoising Algorithm Based on Spatial Kernel Function and Range Kernel Function

A Geiger-mode avalanche photodiode (GM-APD) laser radar range image has much noise when the signal-to-background ratios (SBRs) are low, making it difficult to recover the real target scene. In this paper, based on the GM-APD lidar denoising model of fractional-order total variation (FOTV), the spatial relationship and similarity relationship between pixels are obtained by using a spatial kernel function and range kernel function to optimize the fractional differential operator, and a new FOTV GM-APD lidar range-image denoising algorithm is designed. The lost information and range anomalous noise are suppressed while the target details and contour information are preserved. The Monte Carlo simulation and experimental results show that, under the same SBRs and statistical frame number, the proposed algorithm improves the target restoration degree by at least 5.11% and the peak signal-to-noise ratio (PSNR) by at least 24.6%. The proposed approach can accomplish the denoising of GM-APD lidar range images when SBRs are low.

Noise-suppression algorithm of GM-APD lidar based on Markov random field

Background light easily affects a Geiger-mode avalanche photodiode (GM-APD) laser imaging, detection, and ranging (Lidar), and its detection ability is significantly reduced in strong light environments. Improving imaging performance under a low signal-to-back ratio has become critical. A GM-APD lidar noise-suppression algorithm based on a Markov random field is proposed. The field objective function and prior model are established using similar centre and adjacent pixel features. Both enhance the feature difference between a strong background light and a weak echo signal and improve the ability of weak echo signal reconstruction under an ultra-low signal-to-background ratio (SBR). Imaging experiments of long-distance building targets under varying illumination verified the noise-suppression ability of the algorithm. When the SBR is 0.0055, target recovery can reach 19.40%, and recovery of the whole array image can reach 60.94%. Compared with the sparse Poisson intensity reconstruction algorithm, the image signal-to-noise ratio is improved by 83 dB, and the average depth error was reduced by 36.14 cm. The proposed algorithm improves the imaging performance under ultra-low SBR; it significantly promotes the development of GM-APD lidar all-time applications.

Research on 3D image reconstruction of sparse power lines by array GM-APD lidar

Power lines and other tiny obstacles in the air are deadly hazards to safe aircraft flight. However, existing detection methods have difficulty sensing power lines’ weak radiation signals submerged in noise, making power lines detection an international research hotspot. To solve this problem, this paper proposes the use of array Geiger-mode avalanche photodiode (GM-APD) light detection and ranging (lidar) with single photon detection sensitivity to achieve remote three-dimensional (3D) imaging detection of power lines (GM-PLTR). We focus on solving the problem of noise filtering for sparse power lines under low Signal-to-noise ratio (SNR) conditions and completing 3D image reconstruction. Firstly, we propose a method based on adaptive thresholding and waveform density discrimination combined with spatial dependency to remove the pixel-wise noise, including environmental light, noise echoes from neighboring pixels, and dark count noise. Then we obtain the high SNR depth image of the targets. Secondly, we use an improved DBSCAN algorithm to separate the power lines from the background noise in the depth image to improve the reconstruction effect. Finally, we use a one-directional template matching method to fill in the missing shapes of the power lines. Experimental results show that the algorithm improves the SNR of the power lines echo signal by an average of 2.3 times and achieves sparse power lines imaging detection at 340.95 m. Moreover, the Hough transform confirms the possibility of high-precision detection of power lines, significantly reducing the difficulty of detecting small targets. Finally, it will help unmanned aerial vehicles (UAVs) complete the inspection of power lines.

A spatially correlated fractional integral-based method for denoising geiger-mode avalanche photodiode light detection and ranging depth images

Geiger-mode avalanche photodiode (GM-APD) light detection and ranging (LiDAR) target echo signals are susceptible to interference from atmospheric backscatter, daylight, and other noise, and extracted target depth images contain a large amount of anomalous noise. Accordingly, this paper devises a method based on a spatially correlated fractional integral for denoising GM-APD LiDAR depth images. First, a multi-scale superpixel fusion algorithm is employed to perform null-pixel complementation on a target depth image extracted using histogram statistics. Next, a pixel neighborhood spatial correlation kernel function is used to optimize the Grünwald–Letnikov fractional integral operator to correct the large amount of anomalous noise and thus achieve GM-APD depth image denoising. Simulation and experimental results demonstrate that the denoising performance of the algorithm on GM-APD LiDAR depth images is significantly better than that of median filtering and bilateral filtering, with at least 22.8 % and 4.8 % improvements in the target reduction degree (K) and peak signal-to-noise ratio (PSNR), respectively. In addition, the K and PSNR reach 91.36 % and 18.0241 dB, respectively, with 25 statistical frames in an outdoor imaging experiment. This demonstrates that the algorithm can effectively denoise GM-APD LiDAR depth images with few statistical frames and thus improve the frame rate of GM-APD LiDAR imaging.

Geiger-Mode Operation 4H-SiC Recessed-Window Avalanche Photodiodes Fabricated by N Ion Implantation

In this work, a 4H-SiC n-i-p avalanche photodiode (APD) with n-layer formed by N ion implantation is demonstrated, in which recessed-window structure is used as termination for reducing electrical field crowding effect around the device edge. The APD with 20 μm diameter active region exhibits low dark current of ~5 pA, high gain of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sup> , zero-bias peak quantum efficiency of 53.8 % at 265 nm. Two-dimensional avalanche photocurrent mapping indicates that uniform gain is realized across the device central region while edge-located premature breakdown is effectively suppressed. Since there is no shading effect of top contact metal, close to 100% percent of fill factor is achieved in the multiplication region. The APD can operate in Geiger mode by using a passive quenching circuit. A room temperature single photon detection capability is obtained at 280 nm, when the dark count rate is ~ 28.8 Hz/μm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> .

Adaptive fading Kalman depth estimation with chi-square hypothesis testing for Geiger-mode avalanche photo diode LIDAR

Adaptive fading Kalman depth estimation with chi-square hypothesis testing for Geiger-mode avalanche photo diode LIDAR

Avalanche Photodiodes and Silicon Photomultipliers of Non-Planar Designs

Conventional designs of an avalanche photodiode (APD) have been based on a planar p–n junction since the 1960s. APD developments have been driven by the necessity to provide a uniform electric field over the active junction area and to prevent edge breakdown by special measures. Most modern silicon photomultipliers (SiPM) are designed as an array of Geiger-mode APD cells based on planar p–n junctions. However, the planar design faces an inherent trade-off between photon detection efficiency and dynamic range due to loss of an active area at the cell edges. Non-planar designs of APDs and SiPMs have also been known since the development of spherical APDs (1968), metal-resistor-semiconductor APDs (1989), and micro-well APDs (2005). The recent development of tip avalanche photodiodes (2020) based on the spherical p–n junction eliminates the trade-off, outperforms the planar SiPMs in the photon detection efficiency, and opens new opportunities for SiPM improvements. Furthermore, the latest developments in APDs based on electric field-line crowding and charge-focusing topology with quasi-spherical p–n junctions (2019–2023) show promising functionality in linear and Geiger operating modes. This paper presents an overview of designs and performances of non-planar APDs and SiPMs.

A Fractional-Order Total Variation Regularization-Based Method for Recovering Geiger-Mode Avalanche Photodiode Light Detection and Ranging Depth Images

High-quality image restoration is typically challenging due to low signal–to–background ratios (SBRs) and limited statistics frames. To address these challenges, this paper devised a method based on fractional-order total variation (FOTV) regularization for recovering Geiger-mode avalanche photodiode (GM-APD) light detection and ranging (lidar) depth images. First, the spatial differential peak-picking method was used to extract the target depth image from low SBR and limited frames. FOTV regularization was introduced based on the total variation regularization recovery model, which incorporates the fractional-order differential operator, in order to realize FOTV-regularization-based depth image recovery. These frameworks were used to establish an algorithm for GM-APD depth image recovery based on FOTV. The simulation and experimental results demonstrate that the devised FOTV-recovery algorithm improved the target reduction degree, peak signal–to–noise ratio, and structural similarity index measurement by 76.6%, 3.5%, and 6.9% more than the TV, respectively, in the same SBR and statistic frame conditions. Thus, the devised approach is able to effectively recover GM-APD lidar depth images in low SBR and limited statistic frame conditions.

InGaAs Geiger‐mode three‐dimensional image sensor for flash LIDAR

AbstractThree‐dimensional (3D) image sensors are requested by planetary explorers to detect obstacles around landing sites during the landing process and to measure the relative distance and attitude of an orbiting spacecraft during rendezvous docking procedures. Three‐dimensional image sensors are also requested in many other fields, including as sensors for autonomous vehicles. In flash LIDAR, a sensor acquires 3D images using the diffuse emission of a pulsed laser, making it suitable for applications like obstacle detection and terrain measurement. We fabricated a prototype 3D image sensor with a temporal resolution of 500 ps and dimensions of 128 × 128 pixels using an InGaAs Geiger mode avalanche photodiode, which is capable of counting photons in the eye‐safe band, as the light receiving sensor. This report gives an overview of the prototype sensor and its functions, a detailed evaluation of its time measurement performance, and details of imaging experiments under sunlight.

Research on infrared image guided GM-APD range image recovery algorithm under limited detections

Geiger-mode avalanche photodiode (GM-APD) focal plane array lidar has a high photon-sensitive detection ability and can acquire three-dimensional(3D) distance information. However, high noise intensity and limited detections can easily lead to the loss of target pixels in the range image, and excellent signal extraction and noise suppression technology become crucial. To solve this problem, we propose a guided image recovery (GIR) method which first uses the infrared image information to recover the GM-APD range image. Unlike image fusion technology, which sacrifices the true range value or the objectively existing 3D range image to get the complete image, it cannot only recover the complete image but also guarantee the 3D image is true. The main innovation of the proposed algorithm is to search the missing pixels of the range image based on the boundary information of infrared images and extracts the range values from their own original measurement data according to the adjacent pixels’ information. According to Monte Carlo simulation and experimental data analysis, the proposed method has excellent target recovery, noise suppression, and fidelity performance under limited detections and low SBRs conditions, which provides an important reference for GM-APD lidar real-time detection. It also provides a new research direction for GM-APD lidar range image reconstruction.

Prediction of the Number of Cumulative Pulses Based on the Photon Statistical Entropy Evaluation in Photon-Counting LiDAR.

Photon-counting LiDAR encounters interference from background noise in remote target detection, and the statistical detection of the accumulation of multiple pulses is necessary to eliminate the uncertainty of responses from the Geiger-mode avalanche photodiode (Gm-APD). The cumulative number of statistical detections is difficult to select due to the lack of effective evaluation of the influence of the background noise. In this work, a statistical detection signal evaluation method based on photon statistical entropy (PSE) is proposed by developing the detection process of the Gm-APD as an information transmission model. A prediction model for estimating the number of cumulative pulses required for high-accuracy ranging with the background noise is then established. The simulation analysis shows that the proposed PSE is more sensitive to the noise compared with the signal-to-noise ratio evaluation, and a minimum PSE exists to ensure all the range detections with background noise are close to the true range with a low and stable range error. The experiments demonstrate that the prediction model provides a reliable estimation of the number of required cumulative pulses in various noise conditions. With the estimated number of cumulative pulses, when the signal photons are less than 0.1 per pulse, the range accuracy of 4.1 cm and 5.3 cm are obtained under the background noise of 7.6 MHz and 5.1 MHz, respectively.

Suppressing the influence of GM-APD coherent lidar saturation by signal modulation

Geiger-mode Avalanche Photo Diode (GM-APD) coherent lidar improves coherent detection sensitivity to single photon level, which is more suitable for remote target detection. However, due to the limited pixels, the photon count will be affected by the system saturation, resulting in low utilization of local oscillator (LO), reducing the system's signal-to-noise ratio (SNR). A GM-APD coherent lidar system based on signal modulation is proposed, the method uses an electro-optic modulator to modulate the slope of signal light, then GM-APD coherent detection. Firstly, the detection and optimal parameter model based on signal modulation are derived. Secondly, the effectiveness of this system is analyzed through simulation. Finally, GM-APD coherent detection experiment based on signal modulation is carried out to verify the effectiveness of the system. When the echo position is 2 μs, the pulse width is 200 ns, the number of signal photons is about 8000, LO photons is about 820, signal modulation improves the system SNR by more than two times. It is concluded that the greater influence of saturation on GM-APD coherent lidar, the better signal modulation effect. The proposed scheme improves the utilization rate of LO and SNR from equipment level, to further enhance system detection ability.

3D reconstruction of the dynamic scene with high-speed targets for GM-APD LiDAR

With the advantages of high distance resolution, long detection distance, small size, and low power consumption, Geiger-mode avalanche photodiode (GM-APD) light detection and ranging (LiDAR) has excellent potential for applications such as three-dimensional earth mapping and autonomous driving. The reconstruction for GM-APD LiDAR is based on the statistics of multiple-laser-pulse data, leading to a long imaging time. There are problems such as blurring when the targets are high-speed, which limits its application scope. A reconstruction algorithm of the dynamic scene for GM-APD LiDAR is proposed in this paper to address this problem. Firstly, the motion features (such as velocity and position) of the targets in the scene are extracted by applying the Hough transform and used as a basis to isolate the targets’ echo from the background noise, significantly reducing the noise interference. With these features, the data are corrected for the spatial location to attenuate or eliminate the effects caused by the targets’ motion. Finally, the reconstruction is completed utilizing parameter estimation. Also, we discuss the super-resolution reconstruction capability of this algorithm with sufficient data. Reconstruction results of the scene with targets moving at 100–300 m/s are demonstrated at last. Compared to the conventional algorithms, the peak signal-to-noise ratio (PSNR) is improved by 3–4 dB, and the root-mean-square error (RMSE) of distance is improved by 6–10 times. In addition to a super-resolution reconstruction of the dynamic scene, this method also enables the detection, motion feature extraction, and position prediction of high-speed moving targets in the scene, significantly expanding the application scope of GM-APD LiDAR and having good practical application value.

Multichannel FPGA-based Data Acquisition System for Fan-beam Dual Energy X-ray Absorptiometry

This study aimed to develop a multichannel field programmable gate array (FPGA) based data acquisition (DAQ) system that could process 8 analog signals from a 1 × 8 LYSO array coupled with a Geiger-mode avalanche photodiode (GAPD) for fan-beam dual-energy X-ray absorptiometry (DEXA) system. Each analog input signal was digitized using an 8-channel analog-to-digital converter (ADC) with a 125 MHz sampling rate and an input range of -1.0 to 1.0 V. The 14-bit digital signals were then fed into a Xilinx Virtex-6 FPGA-based evaluation board that implemented digital signal processing logic. The collected low- and high-energy events of each pixel for each input channel were stored in an on-chip block ram-based first-in-first-out (FIFO) module, and then further transmitted to a personal computer (PC) via the USB port. The intrinsic characteristics, spectral responses, and image acquisition were performed. The estimated coefficient of determination (R²) was 0.999 in voltage linearity and no considerable alterations in voltage resolution were observed. The energy resolutions of the peak 59.5 keV (Am-241) were ~28.2 %. Dual-energy peaks were isolated in the X-ray energy spectra. The synchronization between the movement part of the DEXA system and the timing control block inside the FPGA chip was well controlled in various conditions. The DEXA phantom images for each pixel were clearly resolved. This study demonstrated that FPGA with only on-chip memory resources can be used to build a multichannel DAQ system for fan-beam DEXA systems.