A weak near-infrared signal detection device and method in gravitational wave detection

Abstract

The application discloses a weak near-infrared signal detection device and method in gravitational wave detection, solves the problem of detecting extremely weak near-infrared signals, and the existing detection method is prone to losing signals and being interfered by noises, and the response rate of a detector in the near-infrared wave band is low, resulting in low detection precision. The application is arranged in the form of series-parallel combination and multi-stage gating, can flexibly select the best transmission path according to different transmission requirements, improves data transmission efficiency and speed, and improves the flexibility of the system. The multi-stage gating cascade design improves the reliability of the system, reduces the system failure rate, and guarantees the stability and continuity of data transmission.

Description

TECHNICAL FIELD

[0001] The present application relates to a signal detection device and method, in particular to a weak near-infrared signal detection device and method in gravitational wave detection. BACKGROUND

[0002] Near-infrared signal is a kind of electromagnetic radiation wave with longer wavelength and lower energy, which has important application value in the fields of medicine, biology and environmental monitoring. With the continuous progress of science and technology, people's research on near-infrared detection technology has become more and more in-depth. In the research of near-infrared detection technology, the detection of extremely weak near-infrared signal is a key technology, which has important significance in many fields.

[0003] The detection of extremely weak near-infrared signal is widely used in biomedical field for biological tissue imaging, biomolecular detection and disease diagnosis. The detection of extremely weak near-infrared signal can accurately and efficiently obtain the near-infrared detection information of biological tissue, which is used for the research of tissue structure and function. Through the detection of near-infrared detection signal, quantitative analysis of biomolecules and in vivo imaging of biological tissue can be realized, which provides important basis for early diagnosis and treatment of diseases.

[0004] The detection of extremely weak near-infrared signal has important significance for environmental monitoring and pollution control. In recent years, with the increasing seriousness of environmental pollution, people's demand for environmental monitoring and pollution control has become more and more urgent. The detection of extremely weak near-infrared signal can monitor and analyze harmful substances in the environment in real time and accurately, which provides important support for environmental monitoring and pollution control. Through the detection and analysis of near-infrared detection signal, rapid monitoring and tracing of harmful substances in the atmosphere, water and soil can be realized, which provides scientific basis for environmental protection and pollution control.

[0005] The detection of extremely weak near-infrared signal has important significance for the research of material science and engineering field. Near-infrared detection technology is widely used in material characterization, component analysis and performance evaluation in the field of material science and engineering. The detection of extremely weak near-infrared signal can realize accurate analysis and evaluation of the structure, composition and properties of materials, which provides important support for material design and engineering application. Through the detection and analysis of near-infrared detection signal, comprehensive understanding of the microstructure and macroscopic performance of materials can be realized, which provides scientific basis for the research and application of materials.

[0006] Therefore, the detection of extremely weak near-infrared signals is of great significance in the fields of biomedical science, environmental monitoring, and material science. The development and application of this technology will provide important support for human life and health, environmental protection and sustainable development, material innovation and engineering progress. With the continuous progress of technology and the continuous expansion of application, the detection of extremely weak near-infrared signals will show its great potential and value in more fields.

[0007] However, due to the extremely weak intensity of the extremely weak near-infrared signal, its detection becomes a challenging task. First, the scattering of near-infrared light in the element is strong, and the signal intensity decays rapidly. Second, the interference of noise will also affect the accurate detection of the signal. Due to the instability of the light source, environmental interference, and the noise of the instrument itself, various noise components are often mixed in the signal. It is necessary to effectively suppress the noise of the signal to improve the signal-to-noise ratio. However, the current detection equipment still has certain limitations in improving the signal resolution and reducing noise interference.

[0008] The conventional methods to improve the detection accuracy of extremely weak near-infrared signals include increasing the intensity of the near-infrared signal to improve the detection accuracy, and adding a filter and an amplification circuit in the system to build a filter amplification structure with as narrow a bandwidth as possible to filter out noise and achieve the purpose of detecting the signal. However, these conventional methods have problems such as signal loss and noise interference, resulting in low sensitivity and accuracy of signal detection. At the same time, the response rate of the detector in the near-infrared band decreases linearly, the sensitivity decreases rapidly, the detection is difficult, and the detection accuracy decreases significantly. In addition, under the condition that the target signal is extremely weak, the detection is even more difficult. Therefore, it is urgent to develop a method that can effectively improve the detection accuracy of weak near-infrared signals. SUMMARY

[0009] The purpose of the present application is to provide a device and method for detecting weak near-infrared signals in gravitational wave detection, to solve the technical problems of the existing detection methods for extremely weak near-infrared signals, which are prone to signal loss and noise interference, and the response rate of the detector in the near-infrared band is low, resulting in low detection accuracy.

[0010] In order to achieve the above-mentioned purpose, the technical scheme adopted by the present application is as follows:

[0011] A device for detecting weak near-infrared signals in gravitational wave detection, characterized in that it comprises a gating unit, a control unit, a detector, a noise reduction processing unit, and a processor.

[0012] The gating unit is arranged on the optical path of the incident light and comprises a gating gate one, a gating gate two, a gating gate three, a gating gate four, a gating gate five, and controllers a, b, c, d, and e connected to the gating gate one, the gating gate two, the gating gate three, the gating gate four, and the gating gate five, respectively.

[0013] The control unit comprises a central processor and a signal transceiver module connected with each other; the signal transceiver module is further connected with the controller a, the controller b, the controller c, the controller d and the controller e respectively; the central processor outputs corresponding gate action signals; the signal transceiver module is used for transceiving the gate action signals;

[0014] The detection end of the detector corresponds to the output end of the gate one, the gate two, the gate three, the gate four and the gate five, and the output end is connected with the noise reduction processing unit and the processor in sequence; the detector is used for detecting the gate action signals passing through the gate one, the gate two, the gate three, the gate four and / or the gate five;

[0015] The noise reduction processing unit is used for performing noise reduction processing on the signal detected by the detector;

[0016] The processor is used for receiving the detected signal after noise reduction processing.

[0017] Further, the gate unit further comprises a modulation circuit a connected between the controller a and the signal transceiver module, a modulation circuit b connected between the controller b and the signal transceiver module, a modulation circuit c connected between the controller c and the signal transceiver module, a modulation circuit d connected between the controller d and the signal transceiver module, and a modulation circuit e connected between the controller e and the signal transceiver module.

[0018] Further, the noise reduction processing unit comprises an amplifier, a noise reducer and a filter connected in sequence;

[0019] The input end of the amplifier is connected with the output end of the detector;

[0020] The output end of the filter is connected with the input end of the processor.

[0021] A weak near-infrared signal detection method in gravitational wave detection, using the weak near-infrared signal detection device in gravitational wave detection described above, has the particularity that it comprises the following steps:

[0022] Step 1, determining the initial parameters T, ΔT and weight w of each gate; wherein T=2ΔT, error distribution weight w a > w b ≥ w c > w d ≥ w e , and w a + w b + w c + w d + w e =1;

[0023] Step 2, signal detection is performed to obtain a detection signal S m , a detection signal error E is calculated:

[0024] E = S m -S i

[0025] where S i is an ideal signal;

[0026] Step 3, the error E is weightedly distributed to each gate according to the priority of the gate and the current error size, and an error gradient is obtained:

[0027] E a = w a × E

[0028] E b = w b × E

[0029] E c = w c × E

[0030] E d = w d × E

[0031] E e = w e × E

[0032] Step 4, according to the error gradient, a partial derivative of the error of each gate with respect to the corresponding opening time and a partial derivative of the error with respect to the corresponding duration are calculated and respectively as the gradient direction of updating the opening time and the duration of each gate;

[0033] Step 5, based on the gradient direction, the opening time and the duration of each gate are updated by the following formula:

[0034]

[0035] wherein, α is a decay factor, α is greater than 0 and less than or equal to 1;

[0036] Step 6, steps 3-5 are repeated until the detection signal error E i+1 -E i <T, T is a preset threshold, then T i+1 and ΔT i+1 are taken as the optimal opening time and the optimal duration of each gate.

[0037] Advantages of the present application:

[0038] 1. The present application provides a weak near-infrared signal detection device and method in gravitational wave detection, through the form of series-parallel combination, multi-stage gating arrangement, which can flexibly select the best transmission path according to different transmission requirements, improve the data transmission efficiency and speed, and improve the flexibility of the system. The multi-gating cascade design improves the reliability of the system, reduces the system failure rate, and ensures the stability and continuity of data transmission.

[0039] 2. The present application provides a weak near-infrared signal detection device and method in gravitational wave detection, which innovatively designs multiple gating, and combines with the independent control and modulation circuit of each gating, greatly improving the flexibility of signal processing. This design realizes time separation and signal decoupling in the signal transmission process. Different time points are controlled by multiple gating, and each gating can respond to a specific time window. This not only avoids signal conflict, but also effectively reduces the delay phenomenon that may occur in the signal processing process. At the same time, different gating corresponds to different signal channels, which can independently control the transmission and detection of signals. This design ensures the mutual independence of signals, so that the system can process multiple signals of different sources or characteristics at the same time, improving the detection efficiency and sensitivity of the overall system.

[0040] 3. The present application provides a weak near-infrared signal detection method in gravitational wave detection, the opening time and duration of each gating can be dynamically adjusted according to the error of the detection signal to realize adaptive detection. By optimizing and adjusting the opening time and duration of each gating, the system can dynamically correct errors in the signal processing process to ensure that the signal is as close to the ideal state as possible. This real-time correction mechanism can greatly reduce signal distortion. Because the intensity and characteristics of different signals are not the same, the dynamic adjustment of the gating ensures the adaptability to non-uniform or rapidly changing signals, especially in a noisy environment, it can still effectively detect weak signals.

[0041] 4. The present application provides a weak near-infrared signal detection method in gravitational wave detection, by distributing errors to different gating and gradually optimizing the opening and duration of gating. Not only improves the convergence speed of error, but also avoids the local minimum problem that may occur in traditional signal detection devices. Through the continuous updating of errors, the opening and duration of gating gradually approach the optimal state. Each error iteration can make the system closer to the ideal signal capture state, making the signal processing more stable. Because the system performs global weighted distribution of errors each time, the error is not limited to a certain gating. This design ensures the global optimization ability of the error, avoids the local minimum problem that may be caused by traditional methods, and makes the system more robust.

[0042] 5、The signal-to-noise ratio problem is the main technical problem in weak near-infrared signal detection. The weak near-infrared signal detection device in gravitational wave detection provided by the application effectively improves the signal-to-noise ratio of the system through a plurality of noise reduction processing units. The system first amplifies the signal through an amplifier, so that the signal is more easily distinguished and identified in the subsequent processing link. Then, through the cascade processing of the noise reducer and the filter, the environmental noise and instrument noise are further reduced. Different types of noise are usually distributed in different frequency bands, and the filter in the system can selectively suppress noise in different frequency bands. In this way, the interference caused by high-frequency environmental noise and low-frequency light source instability can be effectively suppressed, and the purity and accuracy of the signal can be improved.

[0043] 6、Strong interference, dark and weak environment adaptability. Near-infrared signal detection is often carried out in complex or unstable environments, such as scenes with large temperature changes, weak light or strong stray light interference. The weak near-infrared signal detection device in gravitational wave detection provided by the application is particularly suitable for signal detection in these harsh environments, and the design of multiple signal processing significantly enhances the system's ability to suppress environmental interference, with strong anti-interference ability. In particular, in extreme environments with high optical noise, the system can still maintain high detection accuracy.

[0044] 7、The weak near-infrared signal detection device and method in gravitational wave detection provided by the application mainly uses miniature advanced components to make the entire system small and efficient. Through the improvement and optimization of the signal processing method, the efficiency and performance of the multi-stage gate selection are improved.

[0045] 8、The weak near-infrared signal detection device and method in gravitational wave detection provided by the application adds a modulation circuit composed of buffer, amplifier and other circuit elements in the gate selection circuit to ensure accurate transmission and processing of signals, improve the quality of signals and improve the performance of the circuit.

[0046] 9、The weak near-infrared signal detection device and method in gravitational wave detection provided by the application sends the gating signal to the controller corresponding to each gate through the signal transceiver module, and simultaneously receives the feedback signal of each gate. Through the feedback signal, the opening time and duration of the gate are optimized to achieve optimal gating effect. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 is a structural schematic diagram of an embodiment of a weak near-infrared signal detection device in gravitational wave detection of the application;

[0048] Figure 2 is a distribution diagram of each gate in the embodiment of the application;

[0049] Figure 3is a new method and traditional method test error comparison chart in the embodiment of the application.

[0050] Reference numerals:

[0051] 1-incoming light, 2-gating unit, 3-gating gate one, 4-gating gate two, 5-gating gate three, 6-gating gate four, 7-gating gate five, 8-controller a, 9-controller b, 10-controller c, 11-controller d, 12-controller e, 13-modulation circuit a, 14-modulation circuit b, 15-modulation circuit c, 16-modulation circuit d, 17-modulation circuit e, 18-control unit, 19-central processing unit, 20-signal transceiver module, 21-detecting device, 22-noise reduction processing unit, 23-processor. DETAILED DESCRIPTION

[0052] The technical solutions of the present application will be described clearly and completely in combination with the drawings and embodiments. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments of the present application, all the other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0053] The weak near-infrared signal detection device for gravitational wave detection provided by the embodiment of the present application combines Figure 1 and Figure 2 As shown in the figure, it comprises a gating unit 2, a control unit 18, a detecting device 21, a noise reduction processing unit 22 and a processor 23.

[0054] The gating unit 2 comprises a gating gate one 3, a gating gate two 4, a gating gate three 5, a gating gate four 6, a gating gate five 7, and a controller a 8, a controller b 9, a controller c 10, a controller d 11 and a controller e 12 connected with the gating gate one 3, the gating gate two 4, the gating gate three 5, the gating gate four 6 and the gating gate five 7 respectively; it further comprises a modulation circuit a 13 connected between the controller a 8 and the signal transceiver module 20, a modulation circuit b 14 connected between the controller b 9 and the signal transceiver module 20, a modulation circuit c 15 connected between the controller c 10 and the signal transceiver module 20, a modulation circuit d 16 connected between the controller d 11 and the signal transceiver module 20, and a modulation circuit e 17 connected between the controller e 12 and the signal transceiver module 20.

[0055] The control unit 18 comprises a central processor 19 and a signal transceiver module 20 connected with each other; the signal transceiver module 20 is further connected with the controller a 8, the controller b 9, the controller c 10, the controller d 11 and the controller e 12 respectively; the central processor 19 calculates the difference between the error between the detection signal and the ideal signal and the set threshold value T, controls the corresponding gate action signal, and the signal transceiver module 20 is used for receiving and transmitting the gate action signal.

[0056] The detection end of the detector 21 corresponds to the output end of the gate one 3, the gate two 4, the gate three 5, the gate four 6 and the gate five 7 respectively, and the output end is connected with the noise reduction processing unit and the processor in sequence; the detector 21 is used for detecting the gate action signal passing through the gate one 3, the gate two 4, the gate three 5, the gate four 6 and / or the gate five 7.

[0057] The noise reduction processing unit 22 comprises an amplifier, a noise reducer and a filter connected in sequence; the input end of the amplifier is connected with the output end of the detector 21; the output end of the filter is connected with the input end of the processor 23. The noise reduction processing unit 22 is used for carrying out noise reduction processing on the signal detected by the detector 21.

[0058] The processor 23 is used for receiving the detection signal after noise reduction processing.

[0059] The steps of detecting by using the above-mentioned weak near-infrared signal detection device for gravitational wave detection include:

[0060] 1. Error calculation

[0061] The detection signal S m ;

[0062] The ideal signal S i ;

[0063] The error is denoted as E = S m -S i .

[0064] 2. Adjusting the gate parameters

[0065] Error distribution: distribute the error to each gate, and perform weighted distribution according to the priority of the gate and the current error size.

[0066] Gradient calculation: according to the gradient of the error, the direction and amplitude of the adjustment required by each gate are calculated.

[0067] Parameter update: according to the gradient direction and step length, the opening time and duration of the gate are updated.

[0068] 3. Gradient calculation

[0069] The error distribution weight is: w a >wb ≥w c >w d ≥w e ;

[0070] E a =w a ×E;

[0071] E b =w b ×E;

[0072] E c =w c ×E;

[0073] E d =w d ×E;

[0074] E e =w e ×E;

[0075] Gradient calculation: Calculate the partial derivative of the error with respect to each gate opening time and duration to determine the adjustment direction.

[0076] 4、Parameter update

[0077] According to the gradient direction and step size, the opening time and duration of the gate are updated using the gradient descent method,

[0078] Update formula:

[0079]

[0080] Based on the above update formula, update T a ,ΔT a ,T b ,ΔT b ,T c ,ΔT c ,T d ,ΔT d ,T e ,ΔT e .

[0081] Example:

[0082] 1、Initial gate parameters:

[0083] Gate one: T a = 10ms, ΔT a = 5ms;

[0084] Gate two: T b = 20ms, ΔT b = 10ms;

[0085] Gate three: T c = 30 ms, ΔT c = 15 ms;

[0086] Gate four: T d = 40 ms, ΔT d = 20 ms;

[0087] Gate five: T e = 50 ms, ΔT e = 25 ms;

[0088] Weight: w a = 0.4, w b = 0.2, w c = 0.2, w d = 0.1, w e = 0.1; 2, Parameter calculation

[0089] Probe signal S m = 1.1;

[0090] Error E = 0.1;

[0091] Set threshold T = 0.05.

[0092] 3, Error distribution:

[0093] E a = 0.4 x 0.1 = 0.04;

[0094] E b = 0.2 x 0.1 = 0.02;

[0095] E c = 0.2 x 0.1 = 0.02;

[0096] E d = 0.1 x 0.1 = 0.01;

[0097] E e = 0.1 x 0.1 = 0.01.

[0098] 4, Gradient calculation:

[0099] The partial derivative of the error with respect to the opening time and duration of each gate is:

[0100] 5, Parameter update:

[0101] Update gate parameters:

[0102] T a = 10 - 0.004 = 9.996 ms;

[0103] ΔTa = 5 - 0.004 = 4.996 ms;

[0104] T b = 20 - 0.002 = 19.998 ms;

[0105] ΔT b = 10 - 0.002 = 9.998 ms;

[0106] T c = 30 - 0.002 = 29.998 ms;

[0107] ΔT c = 15 - 0.002 = 14.998 ms;

[0108] T d = 40 - 0.001 = 39.999 ms;

[0109] ΔT d = 20 - 0.001 = 19.999 ms;

[0110] T e = 50 - 0.001 = 49.999 ms;

[0111] ΔT e = 25 - 0.001 = 24.999 ms.

[0112] Using the above algorithm can ensure the continuity and convergence of adjustment, so that the system can effectively reduce the error and achieve higher signal detection accuracy. As shown in the results Figure 3 , it can be seen that the new algorithm adjusts the opening time and duration of each gate by calculating the gradient of the error. Simplify the error distribution and gradient calculation, provide a certain adjustment direction, so that the error can be gradually reduced.

[0113] By reducing the error with each iteration, the ideal signal is gradually approached. This method has good convergence, which can ensure that the error tends to be stable and small after a certain number of iterations.

[0114] Therefore, the method provided by the embodiment has obvious advantages in error adjustment and parameter optimization, has good convergence and high efficiency, so that the new algorithm can more quickly and effectively approach the ideal signal and reduce measurement error in practical application. The traditional method has larger error fluctuation due to its randomness, and lacks systematicness and directionality, and the overall performance is not as stable and efficient as the new algorithm.

[0115] The above merely illustrates the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, any change or replacement within the technical scope disclosed by the present application should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1.A method for detecting weak near-infrared signals in gravitational wave detection, using a weak near-infrared signal detection device in gravitational wave detection, characterized in that: the weak near-infrared signal detection device in gravitational wave detection comprises a gating unit (2), a control unit (18), a detector (21), a noise reduction processing unit (22), and a processor (23); the gating unit (2) is arranged on the light path of incident light (1) and comprises a gating gate one (3), a gating gate two (4), a gating gate three (5), a gating gate four (6), a gating gate five (7), and controllers a (8), b (9), c (10), d (11), and e (12) connected to the gating gate one (3), the gating gate two (4), the gating gate three (5), the gating gate four (6), and the gating gate five (7), respectively; the control unit (18) comprises a central processing unit (19) and a signal transceiver module (20) connected to each other; the signal transceiver module (20) is further connected to the controllers a (8), b (9), c (10), d (11), and e (12); the central processing unit (19) outputs corresponding gating gate action signals; the signal transceiver module (20) is used for transmitting and receiving the gating gate action signals; the detection end of the detector (21) corresponds to the output end of the gating gate one (3), the gating gate two (4), the gating gate three (5), the gating gate four (6), and the gating gate five (7), and its output end is sequentially connected to the noise reduction processing unit (22) and the processor (23); the detector (21) is used for detecting weak near-infrared signals passing through the gating gate one (3), the gating gate two (4), the gating gate three (5), the gating gate four (6), and / or the gating gate five (7); the noise reduction processing unit (22) is used for noise reduction processing of the signals detected by the detector (21); the processor (23) is used for receiving the noise reduction processed detection signals; the method comprises the following steps: Step 3: according to the priority of the gating gate and the current error size, the error E is weighted and distributed to each gating gate to obtain an error gradient: Step 5: based on the gradient direction, the opening time and duration of each gating gate are updated by the following formula: wherein, α is a decay factor, α is greater than 0 and less than or equal to 1. 2.The method according to claim 1, characterized in that: the gating unit further comprises a modulation circuit a (13) connected between the controller a (8) and the signal transceiver module (20), a modulation circuit b (14) connected between the controller b (9) and the signal transceiver module (20), a modulation circuit c (15) connected between the controller c (10) and the signal transceiver module (20), a modulation circuit d (16) connected between the controller d (11) and the signal transceiver module (20), and a modulation circuit e (17) connected between the controller e (12) and the signal transceiver module (20). ​ ​ ​ Step 1, determining initial parameters T, ΔT and weight w of each gate; wherein T=2ΔT, error distribution weight w a > w b ≥ w c > w d ≥ w e , and w a + w b + w c + w d + w e =1; Step 2, signal detection is performed to obtain a detection signal S m , a detection signal error E is calculated E = S m - S i where S i is the ideal signal; ​ E a = w a x E E b = w b xE E c = w c xE E d = w d x E E e = w e x E Step 4. Calculate the partial derivative of the error with respect to the respective on-time of each gate based on the error gradient and the partial derivative of the duration as the gradient direction for updating the respective on-time and duration of each gate, respectively; ​ ​ Step 6, repeat Step 2-Step 5 until the probe signal error E i+1 -E i <T, T is a preset threshold, to T i+1 and ΔT i+1 as the optimal opening time and duration of each gate. ​ ​ 3. The method according to claim 1 or 2, characterized in that: the noise reduction processing unit (22) comprises an amplifier, a noise reducer and a filter connected in sequence; an input end of the amplifier is connected with an output end of the detector (21); an output end of the filter is connected with an input end of the processor (23).

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