A device for detecting extremely weak near-infrared signals

Abstract

This application relates to an extremely weak near-infrared signal detection device. When performing near-infrared band detection, it has high sensitivity and accuracy for detecting extremely weak signals in complex environments. At the same time, it solves the problem that the system response rate drops sharply and the sensitivity decreases rapidly when detecting in the near-infrared band, significantly increasing the difficulty of detection. Its detection accuracy is greatly improved, the detectable signal bandwidth is wider, and the obtained signal quality is higher.

Description

Technical Field

[0001] This application relates to the field of near-infrared detection, specifically to a device for detecting extremely weak near-infrared signals. Background Technology

[0002] Near-infrared (NIR) signal detection is an important technology with wide applications in many fields. The near-infrared wavelength range is generally defined as from 780 nanometers to 2500 nanometers, lying between visible and infrared light. The development of near-infrared signal detection technology has provided a very useful tool for various fields of scientific research, and can be used in a variety of applications, including biomedicine, environmental monitoring, and food quality testing.

[0003] The principle of near-infrared signal detection is based on the absorption and scattering characteristics of near-infrared light by substances. Different substances absorb and scatter near-infrared light to varying degrees, making near-infrared signal detection a very useful analytical tool. By measuring the absorption and scattering characteristics of near-infrared light, information about the sample's composition, concentration, and structure can be obtained. This has led to the widespread application of near-infrared signal detection in many fields, such as drug development, environmental monitoring, and food safety.

[0004] Near-infrared (NIR) signal detection has a wide range of applications. In the biomedical field, NIR light can penetrate skin and tissue, thus enabling non-invasive biomedical imaging. By measuring the absorption and scattering characteristics of NIR light in tissues, information about tissue structure and function can be obtained, which is crucial for disease diagnosis and treatment. In environmental monitoring, NIR signal detection can be used to detect air and water pollutants. By measuring the absorption and scattering characteristics of NIR light in samples, information about pollutant concentration and composition can be obtained, which is vital for environmental protection. In food quality testing, NIR signal detection can be used to detect nutrients, additives, and contaminants in food. By measuring the absorption and scattering characteristics of NIR light in food, information about food quality can be obtained quickly and accurately, which is essential for food safety and quality control.

[0005] In summary, near-infrared signal detection is an important technology with wide applications in many fields. By measuring the absorption and scattering characteristics of near-infrared light, information about sample composition, concentration, and structure can be obtained, which is of great significance for biomedicine, environmental monitoring, and food quality testing. Although near-infrared signal detection technology faces some challenges, with continuous technological development, it is believed that it will have even broader application prospects in the future.

[0006] However, the development of near-infrared signal detection technology still faces some challenges. First, the propagation of near-infrared light in the atmosphere is affected by atmospheric absorption and scattering, which can lead to signal attenuation and increased noise. Due to the instability of the light source, environmental interference, and the noise of the instrument itself, the signal is often mixed with various noise components, affecting the accurate detection. Common methods include increasing the light intensity of the light source and increasing the coupling efficiency between the light source and the sample to increase the intensity of the near-infrared signal, thereby improving detection accuracy. Second, the intensity of near-infrared signals is very weak, requiring highly sensitive detectors and amplifiers for detection. A common method is to incorporate filtering and amplification circuits, constructing a filtering and amplification structure with the narrowest possible bandwidth to filter out noise and achieve the purpose of signal detection. Furthermore, the interpretation and analysis of near-infrared signals is also a challenge, requiring the establishment of accurate models and algorithms to process and interpret the data.

[0007] However, conventional methods often fall short of expectations. Traditional detection methods suffer from problems such as signal loss and noise interference, leading to low sensitivity and accuracy in signal detection. Furthermore, in the near-infrared band, the detector's responsivity drops sharply, sensitivity decreases rapidly, significantly increasing detection difficulty and drastically reducing detection accuracy. This is especially challenging when the target signal is extremely weak. Summary of the Invention

[0008] In order to overcome at least one deficiency in the prior art, this application provides an extremely weak near-infrared signal detection device.

[0009] In a first aspect, a device for detecting extremely weak near-infrared signals is provided, comprising: an optical gating system, a detector, a pre-processing system, a circuit processing system, a phase-locked loop, a phase shifter, an arithmetic unit, a low-pass filter, and a signal processing system; a nonlinear medium is provided in the optical gating system;

[0010] When incident light enters the optical gating system, the nonlinear effect of the nonlinear medium is used to modulate the incident light to obtain a modulated optical signal.

[0011] The modulated optical signal enters the detector for photoelectric conversion to obtain the converted signal;

[0012] The preprocessing system is used to adjust the detector;

[0013] The converted signal enters the circuit processing system, where it is amplified and noise suppressed, and the processed first signal is output.

[0014] The reference signal passes through a phase-locked loop and a phase shifter to obtain the processed second signal;

[0015] The processed first signal and the processed second signal are input into the arithmetic unit and multiplied to obtain the processed signal;

[0016] The processed signal is input into a low-pass filter for filtering to obtain the filtered signal.

[0017] The filtered signal is input into the signal processing system for signal processing to obtain the processed signal.

[0018] In one embodiment, the preprocessing system includes a high-voltage divider detection module and a gain control module.

[0019] In one embodiment, the circuit processing system includes an amplification module, a ripple suppression module, a bandpass filter module, a background noise suppression module, a dark current suppression module, and a random shot noise suppression module.

[0020] In one embodiment, the amplification module employs an operational amplifier with a gain of 40dB and a bandwidth of 100Hz to 1kHz.

[0021] In one embodiment, the ripple suppression module employs a notch filter.

[0022] In one embodiment, the noise floor suppression module employs a second-order notch filter with a notch frequency of 50Hz and a bandwidth of 1Hz.

[0023] In one embodiment, the bandpass filter module uses an active filter with a center frequency of 100Hz and a bandwidth of 200Hz.

[0024] In one embodiment, the nonlinear medium is cadmium telluride with a nonlinear coefficient of 10. -14 cm 2 / W, the nonlinear dielectric has a wafer structure with a size of 8×8mm. 2 The thickness is 1.7mm.

[0025] In one embodiment, the signal processing system is used to perform the following functions:

[0026] For each micro-element in the received filtered signal, a genetic algorithm is used for global search to obtain a preliminary optimized micro-element;

[0027] Gradient descent is used to perform a local search on the initially optimized infinitesimal to obtain a further optimized infinitesimal.

[0028] When the set conditions are met, the current further optimized micro-element is the final optimized micro-element.

[0029] Compared with the prior art, the present application has the following beneficial effects: When performing near-infrared band detection, the extremely weak near-infrared signal detection device of the present application has high sensitivity and accuracy for extremely weak signals in complex environments; at the same time, it solves the problem that the system response rate drops sharply and the sensitivity decreases rapidly when performing near-infrared band detection, which significantly increases the difficulty of detection. Its detection accuracy is greatly improved, the detectable signal bandwidth is wider, and the obtained signal quality is higher. Attached Figure Description

[0030] This application can be better understood by referring to the description given below in conjunction with the accompanying drawings, which, together with the detailed description below, are incorporated in and form part of this specification. In the drawings:

[0031] Figure 1 A schematic diagram of the structure of an extremely weak near-infrared signal detection device according to an embodiment of this application is shown;

[0032] Figure 2 A schematic diagram of the signal detected by the conventional method is shown;

[0033] Figure 3 A schematic diagram of the signals detected by the device of this application is shown.

[0034] Figure label:

[0035] 1-Incident light ray; 2-Optical gating system; 3-Nonlinear medium; 4-Detector; 5-Pre-processing system; 6-High voltage divider control module; 7-Gain control module; 8-Circuit processing system; 9-Amplification module; 10-Ripple suppression module; 11-Bandpass filter module; 12-Number background noise suppression module; 13-Dark current suppression module; 14-Random shot noise suppression module; 15-Arithmetic unit; 16-Reference signal; 17-Phase-locked loop; 18-Phase shifter; 19-Low-pass filter; 20-Signal processing system. Detailed Implementation

[0036] Exemplary embodiments of the present application will be described below with reference to the accompanying drawings. For clarity and brevity, not all features of the actual embodiments are described in the specification. However, it should be understood that many embodiment-specific decisions can be made in the development of any such actual embodiment to achieve the developer’s specific objectives, and these decisions may vary as the embodiments differ.

[0037] It should also be noted that, in order to avoid obscuring this application with unnecessary details, only the device structure closely related to the solution according to this application is shown in the accompanying drawings, while other details that are not closely related to this application are omitted.

[0038] It should be understood that this application is not limited to the described embodiments by virtue of the following description with reference to the accompanying drawings. In this document, embodiments may be combined with each other, features may be substituted or borrowed between different embodiments, and one or more features may be omitted in one embodiment, where feasible.

[0039] This application provides a device for detecting extremely weak near-infrared signals. Figure 1 A schematic diagram of the structure of an extremely weak near-infrared signal detection device according to an embodiment of this application is shown. See also: Figure 1 The device includes an optical gating system 2, a detector 4, a preprocessing system 5, a circuit processing system 8, a phase-locked loop 17, a phase shifter 18, an arithmetic unit 15, a low-pass filter 19, and a signal processing system 20; the optical gating system 2 is equipped with a nonlinear medium 3; the functions of each module are described in detail below.

[0040] Incident light 1 enters optical gating system 2, and the nonlinear effect of nonlinear medium 3 is used to modulate incident light 1 to obtain modulated optical signal.

[0041] The optical gating system 2 consists of a series of optical elements, among which the key element is the nonlinear medium 3. A suitable nonlinear medium is selected based on factors such as its nonlinear coefficient, optical transparency, and thermal stability.

[0042] The modulated optical signal enters detector 4 for photoelectric conversion to obtain the converted signal;

[0043] The preprocessing system 5 is used to adjust the detector 4; specifically, the preprocessing system 5 includes a high voltage divider detection module 6 and a gain control module 7. The high voltage divider detection module 6 is used to perform high voltage divider detection on the detector, and the gain control module 7 is used to control the gain of the detector.

[0044] The converted signal enters the circuit processing system 8 for amplification and noise suppression, and outputs the processed first signal.

[0045] The reference signal 16 passes through the phase-locked loop 17 and the phase shifter 18 to obtain the processed second signal;

[0046] The processed first signal and the processed second signal are input into the arithmetic unit 15 and multiplied to obtain the processed signal;

[0047] The processed signal is input to low-pass filter 19 for filtering to obtain the filtered signal.

[0048] The filtered signal is input into the signal processing system 20 for signal processing to obtain the processed signal.

[0049] In one embodiment, the nonlinear medium 3 is cadmium telluride (CdTe) with a nonlinear coefficient of 10. -14 cm 2 / W, the nonlinear dielectric 3 has a wafer structure with a size of 8×8mm. 2 The thickness is 1.7 mm. The nonlinear medium can cover most of the near-infrared band from 1 μm to 2.5 μm. This size ensures that the beam in the optical system can pass completely through the wafer while maintaining high optical uniformity and nonlinear effects.

[0050] Nonlinear optical effects refer to the phenomenon where, when light passes through a medium, the medium's response is not a simple linear relationship, but rather exhibits nonlinear characteristics as light intensity changes. By utilizing these nonlinear effects, it is possible to modulate light beams, thus providing new methods for optical signal processing.

[0051] Traditional beam modulation methods mainly rely on linear optical effects, such as electro-optic and acousto-optic modulation. These methods have certain limitations when processing weak signals and are difficult to achieve efficient modulation of extremely weak signals.

[0052] The modulation depth (i.e., the degree of modulation of the optical signal) of the electro-optic effect is directly proportional to the strength of the applied electric field. However, when the optical signal is weak, the required electric field strength is relatively large, which may exceed the device's tolerance range, leading to damage to the dielectric or device failure. High electric field strength may introduce electrical noise, thereby affecting the quality of the optical signal, especially for the detection of extremely weak signals.

[0053] The modulation efficiency of the acousto-optic effect is relatively low, especially at high frequencies. This low efficiency makes it difficult to efficiently transmit weak signals. Sound waves attenuate during propagation in a medium, particularly at high frequencies, limiting the modulation range and efficiency of the acousto-optic effect. Effective modulation requires high power, which is undesirable for processing weak signals as high power may introduce additional noise and thermal effects, impacting signal quality. Traditional beam modulation methods suffer from the following problems:

[0054] Signal-to-noise ratio: Weak signals have very low strength and are easily submerged by various noises during modulation, especially in applications with high electric fields and high-power sound waves, where electrical and acoustic noise are more significant, leading to a decrease in the signal-to-noise ratio.

[0055] Modulation depth: Sufficient modulation depth is required for effective modulation of weak signals. However, at low signal strengths, the modulation depth of traditional linear optical effects is limited and cannot effectively enhance the signal.

[0056] Thermal effects and damage risk: High-power electric fields and sound waves can introduce thermal effects, causing the temperature of the medium to rise, which can affect signal quality and risk damaging the medium, especially when processing fragile and weak signals.

[0057] Therefore, traditional linear optical effects exhibit certain limitations when processing extremely weak signals, making it difficult to achieve efficient modulation. However, modulation methods utilizing nonlinear optical effects, by leveraging the nonlinear characteristics of the medium, can effectively modulate weak signals under low power conditions, significantly improving the signal-to-noise ratio and modulation depth, thus overcoming the limitations of traditional methods.

[0058] In this embodiment, nonlinear optical effects are utilized to achieve more efficient modulation of the light beam, which is particularly suitable for processing extremely weak near-infrared signals and has the following technical effects:

[0059] Wide band coverage: Using CdTe nonlinear medium, it can cover most of the near-infrared band from 1μm to 2.5μm, making it more widely applicable.

[0060] High sensitivity and high precision: By optimizing the parameters of the nonlinear medium and improving the optical system, high sensitivity and high precision detection of signals are achieved, significantly improving the detectability of signals.

[0061] This embodiment provides a novel solution for the efficient detection of near-infrared signals by utilizing nonlinear effects and optimizing system parameters, significantly improving the detection performance.

[0062] In one embodiment, the circuit processing system 8 includes an amplification module 9, a ripple suppression module 10, a bandpass filter module 11, a background noise suppression module 12, a dark current suppression module 13, and a random shot noise suppression module 14.

[0063] Specifically, the amplification module 9 uses an operational amplifier to amplify the signal, with a gain of 40dB and a bandwidth of 100Hz to 1kHz.

[0064] Specifically, the ripple suppression module 10 employs a notch filter to eliminate power supply ripple.

[0065] Specifically, the bandpass filter module 11 uses an active filter with a center frequency of 100Hz and a bandwidth of 200Hz.

[0066] The bandpass filtering module is implemented as follows: Wavelet transform is performed in the DSP using a dedicated digital signal processing library. A third-order wavelet transform is employed to reduce noise levels while preserving as many important signal features as possible. The DSP leverages its fast matrix operation capabilities and employs a least-squares algorithm for baseline correction. This removes baseline drift while maintaining the signal's shape. A window size of 20 data points is selected to eliminate the impact of baseline drift and enhance signal detectability.

[0067] Specifically, the noise floor suppression module 12 uses a second-order notch filter with a notch frequency of 50Hz and a bandwidth of 1Hz to accurately suppress 50Hz noise and avoid affecting adjacent frequencies.

[0068] Specifically, the power spectral density of the input signal can be analyzed using Fast Fourier Transform, automatically detecting and locking onto the peak value near 50Hz; the STM32 microcontroller is used to execute the tuning algorithm and control the notch filter.

[0069] Specifically, the dark current suppression module 13 is used to remove dark current and is an existing module.

[0070] Specifically, the random shot noise suppression module 14 is used to remove random shot noise and is an existing module.

[0071] In one embodiment, the signal processing system 20 is used to perform the following functions:

[0072] For each micro-element in the received filtered signal, a genetic algorithm is used for global search to obtain a preliminary optimized micro-element;

[0073] Gradient descent is used to perform a local search on the initially optimized infinitesimal to obtain a further optimized infinitesimal.

[0074] When the set conditions are met, the current further optimized micro-element becomes the final optimized micro-element. All optimized micro-elements constitute the processed signal, which is the more accurate signal obtained. When the set conditions are not met, the above iterative process is repeated, and the processing object of the next iteration is the further optimized micro-element obtained in the current iteration.

[0075] Here, the conditions can be set as follows:

[0076] Calculate the objective function value for the current iteration and determine if the change in the objective function value is less than a preset threshold. If the condition is met, the algorithm is considered to have converged, and the iteration stops. Alternatively, if the number of iterations reaches 100 and convergence has not yet occurred, the iteration stops.

[0077] In this embodiment, the parallel computing power of a multi-core processor is utilized to accelerate the convergence speed of the algorithm during the processing of each micro-element. The algorithm is insensitive to the initial conditions and constraints of the problem; even when the initial conditions or constraints change, the algorithm can adaptively adjust the search range and step size to find a better solution, exhibiting good robustness. The algorithm can simultaneously consider global and local information, thus better avoiding getting trapped in local optima and facilitating the search for the global optimum. The algorithm typically converges to a better solution within a fewer iterations, demonstrating a fast convergence speed.

[0078] Figure 2 This diagram illustrates the signal detected by the conventional method. Figure 3 A schematic diagram of the signal detected by the device of this application is shown. The results demonstrate that this application provides a more accurate and efficient way to process near-infrared signals, especially in applications requiring high sensitivity and high-precision positioning. It effectively removes background noise and baseline drift while maintaining the signal shape, significantly improving signal detectability.

[0079] In summary, this application has the following technical effects:

[0080] 1. Optical gating system is used to realize optical pulse gating, which can significantly reduce the response time, usually in the femtosecond to picosecond range, and can realize fast optical pulse gating; high-precision gating of optical signals can be achieved. By setting parameters such as gating intensity, phase or frequency, precise gating of optical signals can be achieved, thus realizing high-precision gating.

[0081] 2. Utilizing nonlinear optical effects to achieve gating and selection of laser pulses, thereby improving the performance of optical devices. Traditional optical devices are often limited by linear optical effects, making precise control of laser pulses impossible. However, by utilizing nonlinear optical effects, efficient modulation of laser pulses can be achieved, thereby improving the performance and stability of optical devices.

[0082] 3. A pre-control system is used to control the detector in real time and quickly. After a series of circuit processing of the acquired signal, a reference signal is input and calculated with the original signal through lock-in amplification technology, which further improves the detection accuracy of the system.

[0083] 4. Phase-sensitive detection is used for the signal, enabling the detection of extremely weak signals and improving the system's monitoring sensitivity. Simultaneously, it can quickly respond to signal changes, making it suitable for applications requiring real-time detection. It has a low noise level, improving the accuracy and precision of signal detection. It can handle a large signal amplitude range, increasing the dynamic range of signal detection. It also has low power consumption, achieving low-power detection.

[0084] The above descriptions are merely various embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A device for detecting extremely weak near-infrared signals, characterized in that, include: The optical gating system (2), detector (4), preprocessing system (5), circuit processing system (8), phase-locked loop (17), phase shifter (18), arithmetic unit (15), low-pass filter (19) and signal processing system (20) are provided; the optical gating system (2) is provided with a nonlinear medium (3); An incident light ray (1) enters the optical gating system (2), and the nonlinear effect of the nonlinear medium (3) is used to modulate the incident light ray (1) to obtain a modulated optical signal; The modulated optical signal enters the detector (4) for photoelectric conversion to obtain the converted signal; The preprocessing system (5) is used to adjust the detector; The converted signal enters the circuit processing system (8) for amplification and noise suppression, and outputs the processed first signal; The reference signal (16) passes through the phase-locked loop (17) and the phase shifter (18) to obtain the processed second signal; The processed first signal and the processed second signal are input into the arithmetic unit (15) for multiplication to obtain the processed signal; The processed signal is input into the low-pass filter (19) for filtering to obtain the filtered signal; The filtered signal is input into the signal processing system (20) for signal processing to obtain the processed signal; The preprocessing system (5) includes a high voltage divider detection module (6) and a gain control module (7). The circuit processing system (8) includes an amplification module (9), a ripple suppression module (10), a bandpass filter module (11), a background noise suppression module (12), a dark current suppression module (13), and a random shot noise suppression module (14).

2. The apparatus as claimed in claim 1, characterized in that, The amplification module (9) uses an operational amplifier with a gain of 40dB and a bandwidth of 100Hz to 1kHz.

3. The apparatus as described in claim 1, characterized in that, The ripple suppression module (10) uses a notch filter.

4. The apparatus as claimed in claim 1, characterized in that, The background noise suppression module (12) uses a second-order notch filter with a notch frequency of 50Hz and a bandwidth of 1Hz.

5. The apparatus as claimed in claim 1, characterized in that, The bandpass filter module (11) is an active filter with a center frequency of 100Hz and a bandwidth of 200Hz.

6. The apparatus as claimed in claim 1, characterized in that, The nonlinear medium (3) is cadmium telluride with a nonlinear coefficient of 10. -14 cm 2 / W, the nonlinear dielectric has a wafer structure with a size of 8×8mm. 2 The thickness is 1.7 mm.

7. The apparatus as claimed in claim 1, characterized in that, The signal processing system (20) is used to perform the following functions: For each micro-element in the received filtered signal, a genetic algorithm is used for global search to obtain a preliminary optimized micro-element; A gradient descent method is used to perform a local search on the initially optimized infinitesimal to obtain a further optimized infinitesimal. When the set conditions are met, the current further optimized micro-element is the final optimized micro-element.

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