Fourier transform false spectrum identification method and system

Abstract

The application discloses a Fourier transform false spectrum identification method and system, the method is through the zero optical path difference point detection and envelope detection extraction of target interference data, judges the type of target interference data, combines whether effective spectrum components exist in the inversion spectrum data, identifies whether the obtained spectrum data is false spectrum, realizes low complexity, high efficiency and high precision automatic identification of false spectrum obtained by using a Fourier transform spectrum radiometer, lays a good foundation for subsequent false spectrum processing and elimination, and guarantees the accuracy of spectrum data measurement.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of Fourier transform spectral radiometric technology, and in particular to a Fourier transform false spectrum identification method and system. BACKGROUND

[0002] With the rapid development of infrared stealth technology, hypersonic technology, etc., there is an urgent need for high-sensitivity real-time infrared spectral radiometric parameter measurement of low-radiation, fast-flashing targets, etc. Among them, Fourier transform spectral radiometric technology has the advantages of high spectral resolution, high light flux, multi-channel, wide spectral coverage, etc., and is a very important high-resolution spectral analysis technology, especially wide-band infrared spectral radiometric technology, which has been widely used in space remote sensing, target characteristic research, atmospheric detection, material analysis, security and defense, metrology, laboratory, environment, medical treatment, military analysis, criminal investigation, etc.

[0003] Unlike traditional prism, grating spectral type, filter type, etc. The Fourier transform spectral radiometric technology is to obtain the interference data of the target, and after a series of data processing such as Fourier transform on the interference data, the infrared spectral data of the target is obtained. That is, the existing Fourier transform spectral radiometer indirectly obtains the spectral data of the target through Fourier transform, and in this case, there is a problem of Fourier transform false spectrum, that is, based on the obtained interference data of the target, the spectral data can be obtained by Fourier transform, but the spectral data is not real and correct spectral data, that is, false spectral data is obtained, and on this basis, data analysis and processing will lead to incorrect measurement and analysis results.

[0004] In view of the above-mentioned Fourier transform false spectrum, the current false spectrum identification usually adopts manual screening, which is low in efficiency and accuracy. Therefore, how to realize the automatic identification of Fourier transform false spectrum is a technical problem to be solved in the research and application process of Fourier transform spectral radiometric technology. SUMMARY

[0005] In order to solve the above-mentioned problems of the prior art, the present application provides a Fourier transform false spectrum identification method and system, which judges the type of the target interference data by zero optical path difference point detection and envelope detection extraction, identifies whether the obtained spectral data is false spectrum by combining whether the inverse spectral data exists effective spectral component, realizes the low complexity, high efficiency and high precision automatic identification of the false spectrum obtained by the Fourier transform spectral radiometer, lays a good foundation for the subsequent processing and elimination of the false spectrum, and ensures the accuracy of the spectral data measurement.

[0006] In a first aspect, the disclosure provides a Fourier transform false spectrum identification method, comprising:

[0007] Obtaining target interference data, detecting zero optical path difference points of the target interference data;

[0008] Based on the detected zero optical path difference points, using an envelope detection algorithm to extract the envelope of the target interference data;

[0009] Performing spectral inversion on the target interference data to obtain an inverted spectrum;

[0010] Based on the envelope and the inverted spectrum of the target interference data, identifying and determining whether the inverted target spectrum is a false spectrum.

[0011] Further technical solutions, the zero optical path difference point detection comprises:

[0012] The target interference data is input into the hardware detection circuit of the Fourier transform spectrometer, and the approximate position of the zero optical path difference point is output by the hardware detection circuit;

[0013] Taking the approximate position as the center point, the symmetric point number is taken left and right to obtain a segment of data, searching for the maximum point in the segment of data, and taking the maximum point as the zero optical path difference point.

[0014] Further technical solutions, the envelope detection algorithm comprises an envelope detection algorithm based on Morlet wavelet and continuous wavelet transform.

[0015] Further technical solutions, based on the envelope and the inverted spectrum of the target interference data, identifying and determining whether the inverted target spectrum is a false spectrum, comprising:

[0016] Based on the envelope of the target interference data, determining whether the envelope of the target interference data is a trigonometric function form, if the envelope of the target interference data is a trigonometric function form, it is determined that the target interference data is non-effective interference data, otherwise it is effective interference data;

[0017] Based on the inverted spectrum, determining whether there is an effective spectrum component in the inverted spectrum;

[0018] If the target interference data is non-effective interference data and there is an effective spectrum component in the inverted spectrum, it is determined that the target spectrum is a false spectrum.

[0019] Further technical solutions, based on the inverted spectrum, determining whether there is an effective spectrum component in the inverted spectrum, comprising:

[0020] Obtaining the base background spectrum when the Fourier transform infrared spectrometer has no signal input;

[0021] The inversion spectrum is compared with the base background spectrum to determine whether there is effective spectral component in the inversion spectrum; if there is spectral component with spectral line peak value greater than three times the sum of the mean value and the standard deviation value of the background spectrum in the inversion spectrum, it is determined that there is effective spectral component in the inversion spectrum, otherwise, there is no effective spectral component.

[0022] In a second aspect, the present disclosure provides a Fourier transform false spectrum identification system, comprising:

[0023] A target interference data acquisition module is configured to acquire target interference data.

[0024] A target interference data processing module is configured to detect zero optical path difference points of the target interference data, and extract an envelope of the target interference data based on the detected zero optical path difference points using an envelope detection algorithm.

[0025] A target spectrum acquisition module is configured to perform spectral inversion on the target interference data to obtain an inversion spectrum.

[0026] A false spectrum identification module is configured to identify and determine whether the inversion target spectrum is a false spectrum based on the envelope of the target interference data and the inversion spectrum.

[0027] In a further technical solution, the identification and determination of whether the inversion target spectrum is a false spectrum based on the envelope of the target interference data and the inversion spectrum comprises:

[0028] Based on the envelope of the target interference data, it is determined whether the envelope of the target interference data is in the form of a trigonometric function; if the envelope of the target interference data is in the form of a trigonometric function, it is determined that the target interference data is non-effective interference data, otherwise, it is effective interference data.

[0029] Based on the inversion spectrum, it is determined whether there is effective spectral component in the inversion spectrum.

[0030] If the target interference data is non-effective interference data and there is effective spectral component in the inversion spectrum, it is determined that the target spectrum is a false spectrum.

[0031] In a further technical solution, the determination of whether there is effective spectral component in the inversion spectrum based on the inversion spectrum comprises:

[0032] A base background spectrum of the Fourier transform infrared spectrometer without signal input is acquired.

[0033] The inversion spectrum is compared with the base background spectrum to determine whether there is effective spectral component in the inversion spectrum; if there is spectral component with spectral line peak value greater than three times the sum of the mean value and the standard deviation value of the background spectrum in the inversion spectrum, it is determined that there is effective spectral component in the inversion spectrum, otherwise, there is no effective spectral component.

[0034] In a third aspect, the present disclosure also provides an electronic device comprising a memory and a processor, and computer instructions stored on the memory and running on the processor, when the computer instructions are run by the processor, the steps of the method of the first aspect are completed.

[0035] In a fourth aspect, the present disclosure also provides a computer readable storage medium for storing computer instructions, when the computer instructions are executed by a processor, the steps of the method of the first aspect are completed.

[0036] The above one or more technical solutions have the following beneficial effects:

[0037] 1. The present application provides a Fourier transform false spectrum identification method and system, which judges the type of target interference data by zero optical path difference point detection and envelope detection extraction, and identifies whether the obtained spectrum data is a false spectrum by combining whether the inverse spectrum data has effective spectrum components, realizes the low complexity, high efficiency and high precision automatic identification of false spectrum obtained by Fourier transform spectrum radiometer, lays a good foundation for subsequent false spectrum processing and elimination, and ensures the accuracy of spectrum data measurement.

[0038] 2. The present application does not need to update the hardware, only needs to increase the interference data validity detection and identification process in the data processing link, is convenient for automatic identification of false spectrum, and has the characteristics of simplicity and efficiency.

[0039] 3. The method proposed in the present application can be applied to the existing wide-band infrared spectrum radiometer based on the Fourier transform principle, and realizes efficient identification of Fourier transform false spectrum. BRIEF DESCRIPTION OF DRAWINGS

[0040] The drawings accompanying the specification of the present application form a part of the present application, and the illustrative embodiments of the present application and their descriptions serve to explain the present application, and do not constitute an improper limitation on the present application.

[0041] Figure 1 A flow chart of the Fourier transform false spectrum identification method according to the first embodiment of the present application is shown in the figure.

[0042] Figure 2 An interference pattern in which the target interference data in the first embodiment of the present application is a chaotic noise signal is shown in the figure.

[0043] Figure 3 A spectrum pattern based on the target interference data inverse spectrum data in the first embodiment of the present application is shown in the figure.

[0044] Figure 4 A structure schematic diagram of the Fourier transform false spectrum identification system according to the second embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0045] It should be noted that the following detailed description is exemplary in nature and is intended to provide further description of the application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0046] It is also important to note that the terms "or" and "and" as used herein, unless otherwise indicated, are used to mean either phonetic "or", that is, any or all possible combinations of one or more items, or phonetic "and" that is, any combination of all of the items. For example, in the phrase "A and / or B" is intended to mean: "A, and / or B" and any combinations thereof, i.e. A alone, B alone, and / or A and B. As used herein, the term "including" means, and is used interchangeably with, the phrase "including but not limited to". As used herein, the term "and / or" means and is used interchangeably with the phrase "one or both of".

[0047] Embodiment one

[0048] In view of the existing Fourier transform spectroradiometer pointed out in the background art, the spectral data of the target is obtained indirectly by Fourier transform, and in this way, there is a problem of false spectrum of Fourier transform, which further leads to incorrect measurement results. The present embodiment provides a false spectrum recognition method of Fourier transform, as shown in Figure 1 , which comprises the following steps:

[0049] Step S1, obtaining target interference data, and detecting zero optical path difference points of the target interference data;

[0050] Step S2, based on the detected zero optical path difference points, extracting the envelope of the target interference data by using an envelope detection algorithm;

[0051] Step S3, performing spectral inversion on the target interference data to obtain an inversion spectrum;

[0052] Step S4, based on the envelope of the target interference data and the inversion spectrum, identifying and judging whether the inversion target spectrum is a false spectrum.

[0053] When the existing Fourier transform spectroradiometer performs spectral radiation measurement on a target, first, the interference data of the target is obtained, and then Fourier transform is performed on the interference data to obtain the infrared spectral data of the target. In the above process, there is a case where the interference data is a noise signal or other non-effective interference data, but the spectral data can still be obtained by Fourier transform based on the interference data, as shown in Figure 2 , the interference data of the target is a typical chaotic noise signal, but the inversion data obtained by Fourier transform is as shown in Figure 3As shown, there is an effective spectral component in the inversion data, that is, the inversion data is spectral data, but the spectral data is obtained based on a noise signal, so the spectral data is false spectral data. In the prior art, the false spectral data is usually identified by the above artificial identification method, but in fact, the interference data of the target is not so obvious and easy to confirm, therefore, the existing artificial identification method cannot guarantee the accuracy of the identified and judged interference data type, and cannot guarantee the accuracy of the identified false spectrum, in addition, the efficiency of artificial identification is low, and time is wasted.

[0054] To this end, the embodiment provides a Fourier transform false spectrum identification method. First, in step S1, Fourier transform spectral radiometer is used to obtain target interference data, and zero optical path difference (NZPD) point detection is performed on the target interference data. The zero optical path difference point detection is divided into two steps. In the first step, the target interference data is input into the hardware detection circuit of the Fourier transform spectrometer, and the approximate position of the zero optical path difference (NZPD) point is output by the hardware detection circuit. In the second step, the approximate position is taken as the center point, and symmetric points are taken to the left and right to obtain a segment of data. The maximum value point in the segment of data is searched, and the maximum value point is taken as the zero optical path difference (NZPD) point.

[0055] After determining the zero optical path difference point of the target interference data, step S2 is performed. Based on the detected zero optical path difference point, an envelope detection algorithm is used to extract the envelope of the target interference data. In this embodiment, based on the determination of the zero optical path difference point of the target interference data, an envelope detection algorithm based on Morlet wavelet and continuous wavelet transform is used to extract the envelope of the target interference data.

[0056] In step S3, the target interference data is subjected to spectral inversion by Fourier transform to obtain an inversion spectrum.

[0057] In step S4, based on the envelope of the target interference data and the inversion spectrum, it is identified and judged whether the inversion target spectrum is a false spectrum. Specifically, according to the envelope of the target interference data, it is judged whether the envelope of the target interference data is a trigonometric function. If the envelope of the target interference data is a trigonometric function, it is determined that the target interference data is non-effective interference data, otherwise it is effective interference data. According to the inversion spectrum, it is judged whether there is an effective spectral component in the inversion spectrum. If the target interference data is non-effective interference data and there is an effective spectral component in the inversion spectrum, it is determined that the target spectrum is a false spectrum.

[0058] The method for judging whether there is effective spectral component in the inversion spectrum is: using a Fourier transform infrared spectrometer, obtaining a background spectrum without signal input, comparing the inversion spectrum with the background spectrum, and judging whether there is effective spectral component in the inversion spectrum. Specifically, if there is spectral component with a spectral line peak value greater than three times the sum of the mean value and the standard deviation value of the background spectrum in the inversion spectrum, it can be judged that there is effective spectral component in the inversion spectrum, otherwise there is no effective spectral component.

[0059] Through the Fourier transform false spectrum identification method proposed in the embodiment, by processing the target interference data, low complexity, high efficiency and high precision automatic identification of the false spectrum obtained by the Fourier transform spectral radiometer is realized, which lays a good foundation for subsequent processing and elimination of the false spectrum, and ensures the accuracy of spectral data measurement.

[0060] Embodiment two

[0061] The embodiment provides a Fourier transform false spectrum identification system, as shown in Figure 4 , comprising:

[0062] A target interference data acquisition module is configured to acquire target interference data.

[0063] A target interference data processing module is configured to detect a zero optical path difference point of the target interference data, and extract an envelope of the target interference data based on the detected zero optical path difference point by using an envelope detection algorithm.

[0064] A target spectrum acquisition module is configured to perform spectral inversion on the target interference data to obtain an inversion spectrum.

[0065] A false spectrum identification module is configured to identify and judge whether the inversion target spectrum is a false spectrum based on the envelope of the target interference data and the inversion spectrum.

[0066] Embodiment three

[0067] A wide-band infrared spectral radiometer adopts the Fourier transform false spectrum identification method proposed in the embodiment one, and realizes efficient and accurate identification of whether the inversion spectrum obtained based on the target interference data is a false spectrum.

[0068] Embodiment four

[0069] The embodiment provides an electronic device, which comprises a memory and a processor, and computer instructions stored in the memory and running on the processor. When the computer instructions are run by the processor, the steps of the Fourier transform false spectrum identification method described above are completed.

[0070] Embodiment five

[0071] The embodiment also provides a computer readable storage medium for storing computer instructions, which, when executed by a processor, complete the steps in the Fourier transform false spectrum identification method.

[0072] The steps involved in the above embodiments two to five correspond to the method embodiment one, and the specific implementation can refer to the relevant description part of the embodiment one. The term "computer readable storage medium" should be understood as including a single medium or multiple media of one or more instruction sets; it should also be understood as including any medium capable of storing, encoding or carrying instruction sets for execution by a processor and causing the processor to perform any method in the present application.

[0073] Those skilled in the art should understand that each module or step of the present application described above can be realized by a general computer device, alternatively, they can be realized by program codes executable by a computing device, so that they can be stored in a storage device for execution by a computing device, or they can be respectively manufactured into each integrated circuit module, or a plurality of modules or steps among them can be manufactured into a single integrated circuit module to realize. The present application is not limited to any specific combination of hardware and software.

[0074] The above only describes the preferred embodiments of the present application and is not used to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0075] The above describes the specific embodiments of the present application in combination with the accompanying drawings, but is not used to limit the protection scope of the present application. Those skilled in the art should understand that various modifications or changes made on the basis of the technical solutions of the present application without creative labor are still within the protection scope of the present application.

Claims

1. A method for identifying spurious Fourier transform spectra, characterized in that, include: Acquire target interferometric data and perform zero optical path difference detection on the target interferometric data; Based on the detected zero optical path difference point, the envelope of the target interference data is extracted using an envelope detection algorithm; Spectral inversion is performed on the target interferometric data to obtain the inverted spectrum; Based on the envelope and inverted spectrum of the target interferometric data, identify and determine whether the inverted target spectrum is a false spectrum.

2. The Fourier transform spurious spectrum identification method as described in claim 1, characterized in that, The zero-optical-path difference detection includes: The target interferometric data is input into the hardware detection circuit of the Fourier transform spectrometer, and the hardware detection circuit outputs the position of the zero optical path difference point. Using the aforementioned position as the center point, take symmetrical points to the left and right to obtain a data segment. Search for the maximum value point in this data segment and take the maximum value point as the zero optical path difference point.

3. The Fourier transform spurious spectrum identification method as described in claim 1, characterized in that, The envelope detection algorithm includes envelope detection algorithms based on Morlet wavelet and continuous wavelet transform.

4. The Fourier transform spurious spectrum identification method as described in claim 1, characterized in that, The identification and judgment of whether the inverted target spectrum is a spurious spectrum based on the envelope and inversion spectrum of the target interferometric data includes: Based on the envelope of the target interferometric data, determine whether the envelope of the target interferometric data is in trigonometric function form. If the envelope of the target interferometric data is in trigonometric function form, then the target interferometric data is determined to be ineffective interferometric data; otherwise, it is effective interferometric data. Based on the inverted spectrum, determine whether there are effective spectral components in the inverted spectrum; If the target interferometric data is ineffective interferometric data but effective spectral components exist in the inverted spectrum, then the target spectrum is determined to be a false spectrum.

5. The Fourier transform spurious spectrum identification method as described in claim 4, characterized in that, The determination of whether there are effective spectral components in the inverted spectrum based on the inverted spectrum includes: Obtain the background spectrum of the substrate when there is no signal input to the Fourier transform infrared spectrometer; The inverted spectrum is compared with the background spectrum to determine whether there are effective spectral components. If there are spectral components in the inverted spectrum whose spectral peaks are more than three times the sum of the mean and standard deviation of the background spectrum, then the inverted spectrum is considered to have effective spectral components; otherwise, there are no effective spectral components.

6. A broadband infrared radiometer, characterized in that, The method for identifying spurious Fourier transform spectra as described in any one of claims 1-5 is adopted.

7. A Fourier transform spurious spectrum identification system, characterized in that, include: The target interferometric data acquisition module is used to acquire target interferometric data. The target interferometric data processing module is used to perform zero optical path difference detection on the target interferometric data. Based on the detected zero optical path difference, the envelope of the target interferometric data is extracted using an envelope detection algorithm. The target spectrum acquisition module is used to perform spectral inversion on the target interferometric data to obtain the inverted spectrum; The fake spectrum identification module is used to identify and determine whether the inverted target spectrum is a fake spectrum based on the envelope and inversion spectrum of the target interferometric data.

8. The Fourier transform spurious spectrum identification system as described in claim 7, characterized in that, The identification and judgment of whether the inverted target spectrum is a spurious spectrum based on the envelope and inversion spectrum of the target interferometric data includes: Based on the envelope of the target interferometric data, determine whether the envelope of the target interferometric data is in trigonometric function form. If the envelope of the target interferometric data is in trigonometric function form, then the target interferometric data is determined to be ineffective interferometric data; otherwise, it is effective interferometric data. Based on the inverted spectrum, determine whether there are effective spectral components in the inverted spectrum; If the target interferometric data is ineffective interferometric data but effective spectral components exist in the inverted spectrum, then the target spectrum is determined to be a false spectrum.

9. An electronic device, characterized in that: It includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, complete the steps of a Fourier transform spurious spectrum identification method as described in any one of claims 1-5.

10. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, complete the steps of a Fourier transform spurious spectrum identification method as described in any one of claims 1-5.

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