A Method of Range Walk Error Correction in SiPM LiDAR with Photon Threshold Detection

A silicon photomultiplier (SiPM) LiDAR with photon threshold detection can achieve high dynamic performance. However, the number fluctuations of echo signal photons lead to the range walk error (RWE) in SiPM LIDARs. This paper derives the RWE model of SiPM LiDAR by using the LiDAR equation and statistical property of SiPM’s response. Based on the LiDAR system parameters and the echo signal intensity, which is obtained through the SiPM’s photon-number-resolving capability, the RWE is calculated through the proposed model. After that, we carry out experiments to verify its effectiveness. The result shows that the method reduces the RWE in TOF measurements using photon threshold detection from 36.57 cm to the mean deviation of 1.95 cm, with the number of detected photons fluctuating from 1.3 to 46.5.

Using CYGNSS Data to Map Flood Inundation during the 2021 Extreme Precipitation in Henan Province, China

On 20 July 2021, parts of China’s Henan Province received the highest precipitation levels ever recorded in the region. Floods caused by heavy rainfall resulted in hundreds of casualties and tens of billions of dollars’ worth of property loss. Due to the highly dynamic nature of flood disasters, rapid and timely spatial monitoring is conducive for early disaster prevention, mid-term disaster relief, and post-disaster reconstruction. However, existing remote sensing satellites cannot provide high-resolution flood monitoring results. Seeing as spaceborne global navigation satellite system-reflectometry (GNSS-R) can observe the Earth’s surface with high temporal and spatial resolutions, it is expected to provide a new solution to the problem of flood hazards. Here, using the Cyclone Global Navigation Satellite System (CYGNSS) L1 data, we first counted various signal-to-noise ratios and the corresponding reflectivity to surface features in Henan Province. Subsequently, we analyzed changes in the delay-Doppler map of CYGNSS when the observed area was submerged and not submerged. Finally, we determined the submerged area affected by extreme precipitation using the threshold detection method. The results demonstrated that the flood range retrieved by CYGNSS agreed with that retrieved by the Soil Moisture Active Passive (SMAP) mission and the precipitation data retrieved and measured by the Global Precipitation Measurement mission and meteorological stations. Compared with the SMAP results, those obtained by CYGNSS have a higher spatial resolution and can monitor changes in the areas affected by the floods over a shorter period.

Temporal Variability in Acoustic Behavior of Snapping Shrimp in the East China Sea and Its Correlation With Ocean Environments

The snapping shrimp sound is known to be a major biological noise source of ocean soundscapes in coastal shallow waters of low and mid-latitudes where sunlight reaches. Several studies have been conducted to understand the activity of snapping shrimp through comparison with surrounding environmental factors. In this paper, we report the analysis of the sound produced by snapping shrimp inhabiting an area where sunlight rarely reaches. The acoustic measurements were taken in May 2015 using two 16-channel vertical line arrays (VLAs) moored at a depth of about 100 m, located ∼100 km southwest of Jeju Island, South Korea, as part of the Shallow-water Acoustic Variability Experiment (SAVEX-15). During the experiment, the underwater soundscape was dominated by the broadband impulsive snapping shrimp noise, which is notable considering that snapping shrimp are commonly observed at very shallow depths of tens of meters or less where sunlight can easily reach. To extract snapping events in the ambient noise data, an envelope correlation combined with an amplitude threshold detection algorithm were applied, and then the sea surface-bounced path was filtered out using a kurtosis value of the waveform to avoid double-counting in snap rate estimates. The analysis of the ambient noise data received for 5 consecutive days indicated that the snap rate fluctuated with a strong one-quarter-diurnal variation between 200 and 1,200 snaps per minute, which is distinguished from the periodicity of the snap rate reported in the euphotic zone. The temporal variation in the snap rate is compared with several environmental factors such as water temperature, tidal level, and current speed. It is found that the snap rate has a significant correlation with the current speed, suggesting that snapping shrimp living in the area with little sunlight might change their snapping behavior in response to changes in current speed.

Human Falling Recognition Based on Movement Energy Expenditure Feature

Falls in the elderly are a common phenomenon in daily life, which causes serious injuries and even death. Human activity recognition methods with wearable sensor signals as input have been proposed to improve the accuracy and automation of daily falling recognition. In order not to affect the normal life behavior of the elderly, to make full use of the functions provided by the smartphone, to reduce the inconvenience caused by wearing sensor devices, and to reduce the cost of monitoring systems, the accelerometer and gyroscope integrated inside the smartphone are employed to collect the behavioral data of the elderly in their daily lives, and the threshold analysis method is used to study the human falling behavior recognition. Based on this, a three-level threshold detection algorithm for human fall behavior recognition is proposed by introducing human movement energy expenditure as a new feature. The algorithm integrates the changes of human movement energy expenditure, combined acceleration, and body tilt angle in the process of falling, which alleviates the problem of misjudgment caused by using only the threshold information of acceleration or (and) angle change to discriminate falls and improves the recognition accuracy. The recognition accuracy of this algorithm is verified by experiments to reach 95.42%. The APP is also devised to realize the timely detection of fall behavior and send alarms automatically.

Neurometric correlates to sensitive high-frequency sound amplitude modulation detection by mice

Amplitude modulation (AM) is a common feature of natural sounds, including speech and animal vocalizations. Here, we used operant conditioning and in vivo electrophysiology to determine the AM detection threshold of mice as well as its underlying neuronal encoding. Mice were trained in a Go-NoGo task to detect the transition to AM within a noise stimulus designed to prevent the use of spectral side-bands or a change in intensity as alternative cues. Our results indicate that mice, in comparison with other species, detect high modulation frequencies up to 512 Hz exceptionally well, but show poor performance at low frequencies. Our in vivo multielectrode recordings in the inferior colliculus (IC) of both anesthetized and awake mice revealed a few single units with remarkable phase-locking ability to 512 Hz modulation, but not sufficient to explain the good behavioral detection. Using a model of the population response that combined dimensionality reduction with threshold detection, we reproduced the general high-pass characteristics of behavioral detection based on a subset of neurons showing the largest firing rate change (both increase and decrease) in response to AM. Our data thus identify candidate neurons in the IC to explain the high-pass transfer function for AM detection in the mouse.

Fanout of 2 Triangle Shape Spin Wave Logic Gates

Having multi-output logic gates saves much energy because the same structure can be used to feed multiple inputs of next stage gates simultaneously. This paper proposes novel triangle shape fanout of 2 spin wave Majority and XOR gates; the Majority gate is achieved by phase detection, whereas the XOR gate is achieved by threshold detection. The proposed logic gates are validated by means of micromagnetic simulations. Furthermore, the energy and delay are estimated for the proposed structures and compared with the state-of-the-art spin wave logic gates, and 16nm and 7nm CMOS. The results demonstrate that the proposed structures provide energy reduction of 25%-50% in comparison to the other 2-output spin-wave devices while having the same delay, and energy reduction between 43x and 0.8x when compared to the 16nm and 7nm CMOS while having delay overhead between 11x and 40x.

Fanout of 2 Triangle Shape Spin Wave Logic Gates

Having multi-output logic gates saves much energy because the same structure can be used to feed multiple inputs of next stage gates simultaneously. This paper proposes novel triangle shape fanout of 2 spin wave Majority and XOR gates; the Majority gate is achieved by phase detection, whereas the XOR gate is achieved by threshold detection. The proposed logic gates are validated by means of micromagnetic simulations. Furthermore, the energy and delay are estimated for the proposed structures and compared with the state-of-the-art spin wave logic gates, and 16nm and 7nm CMOS. The results demonstrate that the proposed structures provide energy reduction of 25%-50% in comparison to the other 2-output spin-wave devices while having the same delay, and energy reduction between 43x and 0.8x when compared to the 16nm and 7nm CMOS while having delay overhead between 11x and 40x.

Fanout of 2 Triangle Shape Spin Wave Logic Gates

Having multi-output logic gates saves much energy because the same structure can be used to feed multiple inputs of next stage gates simultaneously. This paper proposes novel triangle shape fanout of 2 spin wave Majority and XOR gates; the Majority gate is achieved by phase detection, whereas the XOR gate is achieved by threshold detection. The proposed logic gates are validated by means of micromagnetic simulations. Furthermore, the energy and delay are estimated for the proposed structures and compared with the state-of-the-art spin wave logic gates, and 16nm and 7nm CMOS. The results demonstrate that the proposed structures provide energy reduction of 25%-50% in comparison to the other 2-output spin-wave devices while having the same delay, and energy reduction between 43x and 0.8x when compared to the 16nm and 7nm CMOS while having delay overhead between 11x and 40x.

Performance Enhancement of Opened Resonance Photoacoustic Cells Based on Three Dimensional Topology Optimization

Photoacoustic (PA) spectroscopy techniques enable the detection of trace substances. However, lower threshold detection requirements are increasingly common in practical applications. Thus, we propose a systematic geometry topology optimization approach on a PA cell to enhance the intensity of its detection signal. The model of topology optimization and pressure acoustics in the finite element method was exploited to construct a PA cell and then acquire the optimal structure. In the assessment, a thermo-acoustic model was constructed to properly simulate the frequency response over the range of 0–70 kHz and the temperature field distribution. The simulation results revealed that the acoustic gain of the optimized cell was 2.7 and 1.3 times higher than conventional cells near 25 and 52 kHz, respectively. Moreover, the optimized PA cell achieved a lower threshold detection over a wide frequency range. Ultimately, this study paves a new way for designing and optimizing the geometry of multifarious high-sensitivity PA sensors.