KEYWORDS: Heterodyning, Signal detection, Phase compensation, Target detection, Signal processing, Active optics, Signal to noise ratio, Interference (communication)
Optical heterodyne detection technology is a high-precision detection technology, which is an extension of microwave heterodyne technology in the optical band [1]. Compared with direct detection technology, which can only obtain signal strength information, heterodyne detection technology can obtain the signal from intermediate frequency signals [2]. All information of the frequency, phase and amplitude of the measured signa [3]l, which makes this detection method have many advantages such as high sensitivity and good selectivity [4-5]. In heterodyne detection, the matching state of the local oscillator light field and the signal light field determines the detection sensitivity of the heterodyne detection system [6-7]. This paper proposes a new phase compensation method by pushing the theoretical formula. Reduce the influence of external noise on heterodyne detection. The positioning error is greatly reduced by the proposed phase compensation. The stability of the method is proved through repeated experiments. Repeated experiments proved that the method reduces the deviation from6.289 to 3.814. It provides a new practical idea for the application field of active optical heterodyne detection to solve the problem of decoherence effect of heterodyne signals.
KEYWORDS: Temperature metrology, Calibration, Optical fibers, Raman spectroscopy, Signal attenuation, High temperature raman spectroscopy, Raman scattering, Demodulation, Signal processing, Temperature sensors
With the rapid development of modern society, the advent of the era of big data makes the exchange of information increasingly frequent and important. The distributed fiber Raman temperature measurement system is a brand-new sensing technology that has rapidly developed in recent years. As a transmission medium, it uses spontaneous Raman scattering to acquire back Raman scattering signals through a high-speed acquisition card. Since this signal carries temperature information, this signal is amplified and denoised and then demodulated to obtain a curve with temperature information. In this paper, we study the optical fiber temperature sensing scheme based on Raman scattering and analyze its working principle. By analyzing and comparing the demodulation method of sensor temperature, a method of demodulating temperature at different temperatures by using anti-Stokes fiber temperature as a reference channel is proposed. The relationship between the Raman ratio and the distance is demodulated. Because the traditional calibration scheme fails to take the environmental temperature value into account, this paper adopts a novel dynamic multi-segment fiber temperature calibration method, and verifies the feasibility of the calibration scheme through experiments. The result shows that with the change of the external environment temperature, the temperature of the sensing fiber can be accurately demodulated, the temperature demodulation result is more accurate, the measurement error is less than 1°C. The resulting system is more stable and can adapt to complex environmental changes. Since the light will become soft under high temperature conditions, this paper calculates the relationship between fiber loss coefficient and temperature. It is found that the continuous summation method can better solve the loss problem, thereby effectively improving the system signal-to-noise ratio.
Laser-acoustic joint detection technology is an emerging technology in the field of space-underwater communication, underwater target detection and ocean monitoring in the marine environment. It plays an important role in many new high-end marine equipment manufacturing, deep-sea exploration and security fields. However, accurate detection of multiple sound sources in the case of spectrum aliasing of detection signals has been a technical bottleneck. The purpose of this paper is to extract the underwater sound field information from the sound waves on the water surface, and demodulate the sound frequency of the sound sources close to the underwater frequency. According to the modulation theory of incident laser on the surface of water, this paper introduces the basic principle of laser interferometry to detect sound waves on water surface. This paper proposes a method for detecting the frequency of underwater acoustic signals using optical heterodyne. The expression of the photodetector output current is derived under a plurality of underwater sound source signals. The time domain and frequency domain characteristics of the detected surface wave interference signals are analyzed by simulation. And the feasibility of the method was verified. The results show that the method can detect the frequency and amplitude of the ideal surface wave. In order to obtain a more accurate audible frequency of underwater sound source, this paper proposes a frequency demodulation method based on Hilbert transform. And specific mathematical expressions are derived. This solves the frequency demodulation problem of spectral aliasing of the coherent detection signal. It provides a new method for the detection and processing of underwater acoustic signals.
As an effective way to integrate complementary information in multisensor detection system, image fusion technology has been widely used in robotic vision, medical diagnosis and safety monitoring. At the same time, the dual band infrared detection system has been widely used in the field of guidance and detection.Because dual-band/multi-band infrared detection has the characteristics of wide detection range and multi-target radiation information. Therefore, there is an urgent need of a fusion of the dual-bands infrared images. In order to obtain better image quality, infrared dual-frequency image fusion technology is used to synthesize different radiation information of target and background.In this paper, a new infrared dual-band image fusion with simplified pulse coupled neural network(PCNN) and visual saliency map(VSM) Framework in nonsubampled shearlet domain (NSST) is proposed. In the proposed method, first, the sours images are decomposed into base parts and multiscale and multidirection representations in NSST domain. Then,base parts are fused by VSM fusion approach. For the high-frequency bands are fused by a Simplified pulse coupled neural network model. Finally, the final image is reconstructed by inverse NSST. As a result, the fused image details will be presented more naturally, which is more suitable for human visual perception. The experimental results demonstrate that evaluation quality of the fused images is improved by comparing three objective evaluation factors with three popular fusion methods.This technology is of great significance to the development of image field.
In recent years, small and weak target detection technology is one of the hotspots in information processing technology. However, the detection precision and speed of weak targets still have yet to be improved.
As a branch of machine learning, deep learning has become more and more widely used in various fields. Therefore, this paper improves the deep convolutional networks for the characteristics of weak target detection, including the following three aspects:
Firstly, a dataset dedicated to small and weak target detection is established. The data is sufficient and representative, which is beneficial to improve the quality of the network model. Each image in the dataset has a corresponding label that indicates the name of the image, and the coordinates and width of the target circumscribed rectangle.
Secondly, the image is dilated many times so that the target having only a few pixels is covered by a lot of pixels. The highlighted portion of the image is dilated, and the result image has a larger highlighted area than the original image.
Thirdly, the Faster R CNN algorithm is improved. In this paper, by adjusting the learning rates, a suitable one is determined to get the best network model.
The results show that the average precision on the dataset has improved. The method proposed in this paper is of great significance for the detection of small and weak targets. For the military field, the research on weak target detection has high military value for improving early warning capability and counterattack capability.
Some experiments show that the laser propagation in the actual atmosphere will deviate from the ideal Kolmogorov model. Based on the generalized Huygens-Fresnel principle and non-Kolmogorov turbulence model, the analytical propagation expressions of partially coherent four-petal elliptical Gaussian vortex (PCEPEGV) beams in non-Kolmogorov atmospheric turbulence are derived, and the correctness of the analytical results is verified by simulation. The results show that topological charge number and coherence width play a key role in beam propagation. Large topological charge number, small beam order and large elliptical factor can alleviate the influence of atmospheric turbulence effectively and suppress mode crosstalk in orbital angular momentum mode propagation.
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