Optical filtering device, calculation spectrometer and spectrum reconstruction method

Abstract

The invention discloses an optical filtering device, a calculation spectrometer and a spectrum reconstruction method. The optical filtering device comprises a multi-micro-ring resonator parallel structure formed by cascading a plurality of up-and-down type micro-ring resonators, and each up-and-down type micro-ring resonator is provided with an adjustable phase shifter; the input port is used for separating TE light and TM light through a polarization beam splitter and is connected with one end of the upper waveguide and one end of the lower waveguide of the multi-micro-ring resonator parallel structure respectively, and the other end of the upper waveguide and the other end of the lower waveguide are used for independently outputting the TE light and the TM light through the polarization beam splitter; according to the scheme, the structural parameters of the optical filtering device are adjusted by adopting a reverse design algorithm, so that the spectrum transmission spectral line of the optical filtering device has higher randomness, and an ideal self-correlation width is achieved; the variable filtering behavior is achieved through the adjustable phase shifter, and spectrum reconstruction can be carried out on TE light and TM light respectively.

Description

Technical Field

[0001] The present invention relates to the technical field of computational spectroscopic analysis instruments, and particularly relates to an optical filtering device, a computational spectrometer, and a spectral reconstruction method. Background Art

[0002] Light is a carrier for information transmission. As an important instrument for detecting spectra, spectrometers have very wide applications in various fields such as electronic communication, agricultural production, food manufacturing, aerospace, and geoscience. Traditional spectrometers usually use bulky dispersion elements to disperse unknown spectra of different wavelengths onto detectors in different channels for spectral measurement. This method requires a sufficient number of channels to achieve ideal spectral measurement accuracy, making traditional spectrometers often have a large volume. With the popularization of the Internet of Things and intelligent devices, traditional spectrometers are insufficient to meet the rapidly growing demand for compact, small, and low-cost spectral analysis.

[0003] The emergence of computational spectrometers makes up for the deficiencies of traditional spectrometers. The basic principle of a computational spectrometer is to input the spectrum to be measured into multiple pre-calibrated optical filters. Multiple optical filters with different transmission characteristics sample the signal to be measured respectively. Subsequently, a photodetector converts the optical signal into an electrical signal to measure the intensity of the filtered signal. Finally, spectral reconstruction is performed by solving an inverse problem. The performance of a computational spectrometer greatly depends on the optical filters used. The number of sampling channels required by a computational spectrometer can be much smaller than the number of sampling points within a certain bandwidth. Therefore, a computational spectrometer can maintain a small volume while having high measurement accuracy, and is more suitable for the current high-precision spectral measurement and the demand for miniaturization of spectrometers.

[0004] Currently, the optical filtering devices applied to computational spectrometers can be divided into passive devices and active devices. Passive devices expand the number of filtering channels through a series of beam splitting devices, such as directional couplers, multimode interference couplers (MMIs), etc. Due to the introduction of beam splitting devices, the dynamic range of the spectrometer is reduced, and at the same time, the floor area of the spectrometer is increased and the integration level is reduced. The above defects limit the application scenarios of this type of computational spectrometer. For active devices, they usually have only one filtering channel and need thermo-optical modulation or electro-optical modulation to expand the filtering channels in the time domain, which increases the operational complexity. In addition, currently, computational spectrometers can often only reconstruct single-mode light (TE or TM). Therefore, for computational spectrometers, improving their dynamic range and integration level, reducing their operational complexity, and enabling them to reconstruct multiple modes of light have become an urgent problem to be solved. Summary of the Invention

[0005] In view of the above deficiencies of the prior art, the present invention provides an optical filtering device, a computational spectrometer, and a spectral reconstruction method, which solve the problems of low dynamic range, large footprint, complex operation, and single working mode of current computational spectrometers.

[0006] To achieve the above object, the technical solutions adopted by the present invention are as follows: In a first aspect, an optical filtering device is provided, which includes a parallel structure of multiple microring resonators formed by cascading a plurality of add-drop microring resonators, and an adjustable phase shifter is provided in each add-drop microring resonator; an input port, the input port separates TE light and TM light through a polarization beam splitter and is respectively connected to one ends of the upper and lower waveguides of the parallel structure of multiple microring resonators, and the other ends of the upper and lower waveguides are independently output for TE light and TM light through a polarization beam splitter.

[0007] Further, the resonant cavity in the add-drop microring resonator is a closed structure connected end to end.

[0008] Further, the adjustable phase shifter is arranged in the resonant cavity of the add-drop microring resonator and the straight waveguide connecting the add-drop microring resonators.

[0009] Further, each parallel branch of the parallel structure of multiple microring resonators includes one add-drop microring resonator or multiple series-connected add-drop microring resonators.

[0010] In a second aspect, a computational spectrometer is provided, which includes an optical filtering device, a light source, and a photodetector. The optical filtering device expands the number of filtering channels through time-domain phase modulation N The calculation formula is: N =2 p n Wherein, p is the number of phase states that the add-drop microring resonator can change through phase modulation, n is the number of add-drop microring resonators.

[0011] In a third aspect, a spectral reconstruction method for a computational spectrometer is provided, which includes the following steps: S1: A broadband light source separates TE light and TM light through a polarization beam splitter, and respectively inputs them through the corresponding input ports, and the optical filtering device respectively characterizes the filtering characteristics; S2: TE light and TM light are respectively separated by a polarization beam splitter at the output end, and sampled by the corresponding photodetectors to obtain the corresponding output power values; S3: TE light and TM light are respectively subjected to spectral reconstruction based on the corresponding filtering characteristics and output power values.

[0012] Further, before performing step S1, the structural parameters of the optical filtering device are adjusted by a reverse design algorithm, and the adjustment method is as follows: A1: Initialize the structural parameters of the optical filtering device. The structural parameters include the perimeter of the resonator cavity in the add-drop micro-ring resonator, the coupling coefficients between the resonator cavity and the upper and lower waveguides, and the spacing of the add-drop micro-ring resonator; A2: Calculate the autocorrelation width of the filtering spectrum line of the optical filtering device; A3: Randomly iterate the structural parameters of the optical filtering device and recalculate the autocorrelation width of the filtering spectrum line; A4: If the autocorrelation width after the iteration of the structural parameters is less than the autocorrelation width before the iteration of the structural parameters, then perform step A5; otherwise, perform step A6; A5: Retain the structural parameters after the iteration and return to step A3; A6: Retain the structural parameters before the iteration and determine whether the number of iterations reaches the set threshold. If not, return to step A3; if so, output the corresponding structural parameters.

[0013] The beneficial effects of the present invention are as follows: 1. The optical filtering device of this solution has more adjustable structural parameters, and a reverse design algorithm is used to adjust the structural parameters of the optical filtering device, making its spectral transmission spectrum line have greater randomness, so as to achieve an ideal autocorrelation width; the optical filtering has two filtering channels, achieving the effect of one-way input and two-way output. Under the same scanning time, the filtering channels of the optical filtering device can be doubled; the optical filtering device can reconstruct TE light and TM light simultaneously, or can reconstruct TE light and TM light separately.

[0014] 2. The resonator cavity in the add-drop micro-ring resonator is a closed structure connected end to end, which can make the coupling region lengths between the resonator cavity and the upper and lower waveguides different. By changing the coupling length, the coupling coefficient can be changed, so as to achieve a larger coupling coefficient change range.

[0015] 3. Each add-drop micro-ring resonator is equipped with an adjustable phase shifter, and the effective refractive index of the micro-ring resonator can be changed through the adjustable phase shifter, so that the filtering device exhibits different spectral characteristics in the time domain, thereby expanding the number of filtering channels in the time domain. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a structural schematic diagram of the optical filtering device of this solution.

[0017] Figure 2 It is an expanded structural schematic diagram of the optical filtering device of this solution.

[0018] Figure 3 It is a flowchart for adjusting the structural parameters of the optical filtering device.

[0019] Figure 4 It is the filtering curve graph under different phase states.

[0020] Figure 5 It is the reconstruction test graph of the spectrometer for broadband spectral signals.

[0021] Figure 6 It is the reconstruction test graph of the spectrometer for narrowband spectral signals.

[0022] Among them, 1. Up / down-loading micro-ring resonator, 2. Tunable phase shifter, 3. Polarization beam splitter. Specific embodiments

[0023] The following describes the specific embodiments of the present invention to facilitate those skilled in the art of this technology to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art of this technology, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are within the scope of protection.

[0024] As Figure 1 shown, the optical filtering device of this solution includes a parallel structure of multiple micro-ring resonators formed by cascading several up / down-loading micro-ring resonators 1; an input port, the input port separates TE light and TM light through a polarization beam splitter 3 and is respectively connected to one ends of the upper and lower waveguides of the parallel structure of multiple micro-ring resonators, and the other ends of the upper and lower waveguides are both independently output TE light and TM light through a polarization beam splitter 3, and then spectral reconstruction is performed on TE light and TM light respectively.

[0025] Each up / down-loading micro-ring resonator 1 is equipped with a tunable phase shifter 2 in its resonant cavity. For the up / down-loading micro-ring resonator 1, the resonant equation it satisfies is:

[0026]

[0027] Among them, λ represents the resonant wavelength, R is the radius of the micro-ring, n c represents the effective refractive index, m is the resonant order (positive integer); through the tunable phase shifter 2, the effective refractive index of the up / down-loading micro-ring resonator 1 can be changed, so that the filtering device shows different spectral characteristics in the time domain, thereby expanding the number of filtering channels in the time domain.

[0028] Assume that the number of up / down-loading micro-ring resonators 1 is n , and the number of phase states that the tunable phase shifter 2 can change for each up / down-loading micro-ring resonator 1 through phase modulation isp , then the number of filter channels that a physical channel can expand in the time domain is p n , for the present invention, there are two physical channels, namely a through-end and a download-end, in the filtering device. Then, the filter channels that can be expanded in the time domain N , satisfying N =2 p n .

[0029] The structural parameters of the optical filtering device include the perimeter of the resonator cavity in the up / down-loading micro-ring resonator 1, the coupling coefficients between the resonator cavity and the upper and lower waveguides, and the spacing d1 of the up / down-loading micro-ring resonator 1. Moreover, the perimeter of the resonator cavity, the coupling coefficients between the resonator cavity and the upper and lower waveguides, and the spacing of each up / down-loading micro-ring resonator 1 are different; assuming the number of micro-ring resonators is n (n > 1 ) , then the number of adjustable parameters of the entire optical filtering device is 4n- 1.

[0030] The up / down-loading micro-ring resonator 1 changes the coupling coefficient by changing the coupling lengths L1 and L2, so as to achieve a larger coupling coefficient change range. Therefore, the coupling region lengths between the resonator cavity and the upper and lower waveguides in each up / down-loading micro-ring resonator 1 are different, and the resonator cavity is a closed structure with the head and tail connected; at the same time, the upper and lower waveguides can be designed in a combination of straight waveguides and curved waveguides, so that the perimeter of the up / down-loading micro-ring resonator 1 has a larger change range.

[0031] As Figure 2 shown, each parallel branch of the multi-micro-ring resonator parallel structure can be expanded into two series-connected up / down-loading micro-ring resonators 1.

[0032] As Figure 3 shown, in this solution, the structural parameters of the optical filtering device are adjusted through an inverse design algorithm, so that its spectral transmission spectral line has greater randomness, so as to achieve an ideal autocorrelation width. The adjustment method is as follows: A1: Initialize the structural parameters of the optical filtering device. The structural parameters include the perimeter of the resonator cavity in the up / down-loading micro-ring resonator 1, the coupling coefficients between the resonator cavity and the upper and lower waveguides, and the spacing of the up / down-loading micro-ring resonator 1; A2: Calculate the autocorrelation width of the filtering spectral line of the optical filtering device through the autocorrelation function; the calculation formula of the autocorrelation function is:

[0033] Among them, is the intensity of the transmission spectrum, <...> λ is to take the average value within a specific wavelength band, is the wavelength shift, and the full width at half maximum (HWHM) of is the autocorrelation width; A3: The structural parameters of the random iterative optical filtering device, and recalculate the autocorrelation width of the filtered spectral line; A4: If the autocorrelation width after the iteration of the structural parameters is less than the autocorrelation width before the iteration of the structural parameters, then execute step A5, otherwise, execute step A6; A5: Retain the structural parameters after the iteration, and return to step A3; A6: Retain the structural parameters before the iteration, and determine whether the number of iterations reaches the set threshold. If not, then return to step A3; if so, output the corresponding structural parameters.

[0034] This solution also provides a computational spectrometer, which includes an optical filtering device, a light source, and a photodetector, In specific implementation, the optical filtering device and the detector array can be a monolithic integrated chip, which is fabricated on a common substrate material through a compatible process; they can also be realized by independent chips respectively and integrated into a system through packaging. Its fabrication process is compatible with the widely used CMOS process, making the overall processing difficulty of the device lower; at the same time, the loss of the device itself is small and the working bandwidth is large, which can further improve the practicability of the computational spectrometer.

[0035] The spectral reconstruction method of the computational spectrometer in this solution includes the following steps: S1: The broadband light source separates TE light and TM light through a polarization beam splitter 3, and inputs them through the corresponding input ports respectively, and the optical filtering device respectively performs filtering characteristic characterization; S2: The TE light and TM light are separated by the polarization beam splitter 3 at the output end respectively, and sampled by the corresponding photodetectors to obtain the corresponding output power values; S3: The TE light and TM light perform spectral reconstruction respectively by the corresponding filtering characteristics and output power values.

[0036] After the unknown spectrum in this solution is sampled by the optical filtering device, it is then converted into an electrical signal by the photodetector array, and finally, the unknown spectrum can be spectrally reconstructed through relevant algorithms such as compressive sensing, truncated inversion, and deep learning.

[0037] In order to verify the autocorrelation of the filtering spectrum of the optical filtering device and the mutual correlation of the filtering spectrum between different filtering channels, it is assumed that the optical filtering device is composed of six up-downloading microring resonators 1 in cascade. In actual applications, the number can be adjusted at will. It is assumed that each up-downloading microring resonator 1 has two phase states of 0 and π. According to the previous discussion, a total of 128 groups of filtering channels can be generated at the through end and the download end. The scattering matrix method is used to simulate and calculate the above optical filtering device in Matlab. The microring radius varies between 15-40 microns, the coupling coefficient varies between 0.2-0.85, and the microring spacing varies between 150-300um to avoid thermal crosstalk as much as possible.

[0038] like Figure 4 As shown, it shows the spectral responses of two filter channels randomly selected from 128 filter channels; observing the waveforms, it can be seen that the randomness of each waveform itself is relatively large, that is, the autocorrelation is small, and the calculated autocorrelation width is 0.15; at the same time, the difference between the two waveforms is large, that is, the cross-correlation is small.

[0039] According to the above analysis, by changing the circumference of each up-down type microring resonator 1 in the optical filtering device proposed in this scheme, the coupling coefficient between the up-down type microring resonator 1 and the upper and lower waveguides, and the spacing between the up-down type microring resonators 1, the transmission spectrum of the device itself can be changed, thereby ensuring that the randomness of the transmission spectrum of each device itself is relatively large. The autocorrelation width is calculated to be 0.15, and the difference in the transmission spectra between different devices is relatively large, and the mutual correlation is relatively small, so that the optical filtering device meets the requirements for the design of a computational spectrometer.

[0040] In this scheme, the spectrum to be measured in a single mode (TE or TM) is divided into two paths, the through end and the download end, after passing through the optical filter device; the number of filtering channels can be expanded in the time domain through the adjustable phase shifter 2; assuming that the number of sampling points within the working bandwidth is M , then the number of filter channels N Can be much smaller than the number of sampling points M ; The spectrum to be measured passes N After sampling through the filter channel, the photodetector performs photoelectric conversion on the collected optical signal and converts it into an electrical signal. Its output power value can be expressed as: ;

[0041] in, is the transmission matrix after N-way sampling; For the i The transmission spectrum of the optical signal. i =1,2,……,N; To passN The output power value after sampling in the path filtering channel; An unknown spectral signal with the number of samples being M.

[0042] By solving the above non-homogeneous linear equations, the unknown spectral signal can be reconstructed. Among them, the number of equations is much less than the number of unknowns, which is the advantage of the computational spectrometer compared with the traditional spectrometer.

[0043] In Matlab, numerical simulation is carried out on the computational spectrometer. Actually, six up / down-loading micro-ring resonators 1 are adopted. Each up / down-loading micro-ring resonator 1 has two phase states, and the number of generated filtering channels is 128. Spectral reconstruction is carried out on the broadband signal and the narrowband signal respectively. As Figure 5 shown, it shows the result of reconstructing the broadband signal; as Figure 6 shown, it shows the result of reconstructing two narrowband signals with a spacing difference of 20 pm. The reconstructed spectrum is basically completely consistent with the actual spectrum. The spectral resolution can reach 20 pm. The computational spectrometer shown has doubled the number of filtering channels generated compared with a single-channel spectrometer under the same sampling time, and at the same time, the achieved spectral resolution far exceeds that of general computational spectrometers.

Claims

1. An optical filtering device, characterized in that, Comprising: A parallel structure of multiple microring resonators formed by cascading a plurality of up-down-loading microring resonators, and an adjustable phase shifter is provided for each up-down-loading microring resonator; An input port, the input port separates TE light and TM light through a polarization beam splitter, and is respectively connected to one end of the upper and lower waveguides of the parallel structure of multiple microring resonators, and the other ends of the upper and lower waveguides are independently output for TE light and TM light through a polarization beam splitter.

2. The optical filtering device according to claim 1, characterized in that, The resonator cavity in the up-down-loading microring resonator is a closed structure with the head and tail connected.

3. The optical filtering device according to claim 1, wherein The adjustable phase shifter is arranged in the resonator cavity of the up-down-loading microring resonator and the straight waveguide connecting the up-down-loading microring resonators.

4. The optical filtering device according to claim 1, wherein Each parallel branch of the parallel structure of multiple microring resonators includes one up-down-loading microring resonator or multiple series-connected up-down-loading microring resonators.

5. A computing spectrometer, characterized in that, Comprising the optical filtering device, light source, and photodetector described in any one of claims 1-4, the optical filtering device expands the number of filtering channels through time-domain phase modulation N The calculation formula of which is: N =2 p n wherein, p is the number of phase states that can be changed by phase modulation of the add-drop microring resonator, n is the number of add-drop microring resonators.

6. A spectral reconstruction method for a computational spectrometer according to claim 5, characterized in that, Including the following steps: S1: A broadband light source separates TE light and TM light through a polarization beam splitter, and is respectively input from the corresponding input ports, and the filtering characteristics are respectively characterized by an optical filtering device; S2: TE light and TM light are respectively separated by a polarization beam splitter at the output end, and are sampled by the corresponding photodetectors to obtain the corresponding output power values; S3: TE light and TM light are respectively subjected to spectral reconstruction by the corresponding filtering characteristics and output power values.

7. The spectral reconstruction method of the computational spectrometer according to claim 6, characterized in that, Before performing step S1, the structural parameters of the optical filtering device are adjusted by a reverse design algorithm, and the adjustment method is: A1: Initialize the structural parameters of the optical filtering device, and the structural parameters include the perimeter of the resonator cavity in the up-down-loading microring resonator, the coupling coefficients between the resonator cavity and the upper and lower waveguides, and the spacing between the up-down-loading microring resonators; A2: Calculate the autocorrelation width of the filtering spectrum line of the optical filtering device through the autocorrelation function; A3: Randomly iterate the structural parameters of the optical filtering device, and recalculate the autocorrelation width of the filtering spectrum line; A4: If the autocorrelation width after the iteration of the structural parameters is less than the autocorrelation width before the iteration of the structural parameters, then perform step A5, otherwise, perform step A6; A5: Retain the structural parameters after the iteration, and return to step A3; A6: Retain the structural parameters before the iteration, and determine whether the number of iterations reaches the set threshold. If not, return to step A3; if so, output the corresponding structural parameters.

8. The method for spectral reconstruction of a computational spectrometer according to claim 7, wherein The calculation formula of the autocorrelation function is: Among them, is the intensity of the transmission spectrum, <...> λ is to calculate the average value within a specific wavelength band, is the wavelength shift, The full width at half maximum of is the autocorrelation width.

9. The spectral reconstruction method of the computational spectrometer according to claim 6, wherein The calculation formula of the output power value is: ； Among them, is the transmission matrix after N-channel sampling; is the i transmission spectral line of the i th optical signal, where N = 1, 2, ……, N; is the output power value after sampling through the N -channel filtering channel; is an unknown spectral signal with the number of samples being M. By solving , the unknown spectral signal can be reconstructed.

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