Optimization method for unequal period arrangement of optical phased array

Abstract

The invention relates to an optimization method for unequal period arrangement of an optical phased array. The optimization method comprises the following steps: acquiring a far-field light intensity distribution expression of the optical phased array; setting a sequence formed by the spacing of each channel in the optical phased array as a vector to be optimized; and taking the vector to be optimized as an immune individual, and solving by using an immune optimization algorithm to obtain an optimal channel spacing, so that the optical phased array has the lowest grating lobe suppression ratio in a preset scanning range. According to the invention, grating lobe suppression under a large waveguide spacing can be realized, the emission aperture is improved, and the beam divergence angle is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of optical phased arrays, and in particular to an optimization method for non-equiperiodic arrangement of optical phased arrays. Background Art

[0002] Optical phased array (OPA) is a fully solid-state beam scanning technology that does not contain any mechanical structure and can point to any direction within the field of view. It also has a small beam divergence angle and flexible beam switching, which has a huge and broad prospect in the field of LiDAR. However, the traditional optical phased array with uniformly arranged antennas has limited market scope due to the appearance of grating lobes. In order to avoid beam confusion and ensure a large field of view, the spacing between antennas needs to be reduced, which may cause crosstalk between waveguides. In order to take into account the divergence angle, the number of antennas must be increased, but the drive control of OPA will become extremely complicated. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide an optimization method for the non-uniform periodic arrangement of an optical phased array, which can achieve grating lobe suppression under large waveguide spacing, while increasing the emission aperture and reducing the beam divergence angle.

[0004] The technical solution adopted by the present invention to solve the technical problem is: to provide an optimization method for the non-equiperiodic arrangement of an optical phased array, comprising the following steps:

[0005] Obtain the far-field light intensity distribution expression of the optical phased array;

[0006] Setting a sequence formed by the spacings of the channels in the optical phased array as a vector to be optimized;

[0007] The vector to be optimized is taken as an immune individual, and an immune optimization algorithm is used to solve and obtain the optimal spacing between each channel, so that the optical phased array has the lowest grating lobe suppression ratio within a preset scanning range.

[0008] The affinity function of the immune optimization algorithm is the grating lobe suppression ratio at the maximum deflection angle within the global scanning range.

[0009] The far-field light intensity distribution expression is: Wherein, E is the far-field light intensity distribution of the optical phased array, N is the number of array elements, and A is i is the amplitude strength of the i-th array element, f is the array element factor, x i is the position of the i-th array element, λ is the operating wavelength, θ s is the deflection angle, and θ is the field of view angle of the optical phased array scanning.

[0010] The grating lobe suppression ratio is calculated by using the far-field light intensity distribution expression.

[0011] The immune optimization algorithm is used to solve the optimal channel spacing, specifically:

[0012] Set the population size, the dimension of immune individuals and the number of iterations;

[0013] Identify antigens and create an initialized population; wherein each immune individual in the population is a sequence formed by the spacing of each channel in the optical phased array;

[0014] Calculate the affinity function of each immune individual in the population, and update the local best immune individual and the global best immune individual;

[0015] Determine whether the termination condition is met;

[0016] If it is not satisfied, immune individuals with affinity values ​​exceeding the threshold are selected for memory, and the suppression and promotion of immune individuals are performed;

[0017] Perform immune operations to update the population and recalculate the affinity function of each immune individual in the population until the termination condition is met.

[0018] The termination condition is whether the current number of iterations reaches the set number of iterations.

[0019] Beneficial Effects

[0020] Due to the adoption of the above technical scheme, the present invention has the following advantages and positive effects compared with the prior art: the present invention takes the array element factor into consideration in the immune optimization stage and substitutes it into the algorithm for optimization, and combines the influence of the main light beam being weakened by the directional factor when it is deflected in the actual scene. The obtained far-field light intensity distribution can better characterize the actual scanning condition. The non-periodic optical phased array optimized by the algorithm has a low grating lobe suppression ratio within the set scanning range, and can increase the emission aperture and reduce the beam divergence angle. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a flow chart of an optimization method for non-equiperiodic arrangement of an optical phased array according to an embodiment of the present invention;

[0022] Figure 2 Flow chart of the immune optimization algorithm in the embodiment of the present invention. DETAILED DESCRIPTION

[0023] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms fall within the scope limited by the appended claims of the application equally.

[0024] The embodiments of the present invention relate to an optimization method for non-equiperiodic arrangement of an optical phased array, such as Figure 1 As shown in the figure, it is mainly divided into two stages: modeling and optimization.

[0025] The modeling stage refers to modeling the optical phased array and obtaining the far-field light intensity expression, which includes:

[0026] Step 1: Express the element factor of the optical phased array in a formula and substitute it into the far-field light intensity expression of the optical phased array.

[0027] The key part of the optical phased array to achieve beam scanning is the transmitting array. Each array element is a transmitting antenna of the phased array. Each transmitting antenna is controlled by the phase modulator in front, so that it has a specific phase. The n transmitting antennas form an array, and the final effect is to form a converging main beam (scanning main beam) at a certain angle. Among them, the spacing between the i-th and i+1-th channels is recorded as di.

[0028] The far-field light intensity expression can be used to solve the light intensity distribution of the optical phased array within the range of ±90° at a specified deflection angle and the grating lobe suppression ratio at the deflection angle. When the array element factor is set to f, the far-field light intensity distribution expression of the optical phased array is:

[0029]

[0030] Where, E is the far-field light intensity distribution of the optical phased array, and its independent variable θ is [-90°, 90°]; N is the number of array elements (i.e., the number of channels); A i is the amplitude strength of the i-th array element; f is the array element factor, which is a function of an independent variable θ of [-90°, 90°] and is determined by the structural parameters of the transmitting antenna; x i is the position of the i-th array element; λ is the operating wavelength; θ s is the deflection angle, θ is the field of view angle of the phased array scanning; in this embodiment, is the phase difference between array elements.

[0031] The optimization stage refers to the process of using the immune optimization algorithm to obtain a one-dimensional array [d1, d2, d3, …, d N-1 ], so that the optical phased array arranged according to the array can have the lowest grating lobe suppression ratio within the preset scanning range, specifically including:

[0032] Step 2: Set the parameters of the optical phased array, including the maximum channel spacing d of the aperiodic array max and the minimum channel spacing d min , the number of array elements N, the set scanning range [-θ s ,+θ s ]. Among them, the maximum channel spacing dmax and the minimum channel spacing d min is the range of the channel spacing, d1, d2, d3, ..., d N-1 All randomly selected values ​​are within this range; the number of array elements N, the set scanning range [-θ s ,+θ s ] defines the expectation of obtaining an N-element optical phased array and in [-θ s ,+θ s ] to achieve the lowest grating lobe suppression ratio.

[0033] Step 3: Set the relevant parameters of the immune optimization algorithm, including: population size NP, number of iterations G, local best immune individual Na, global best immune individual Bestf, affinity function F. Among them, immune individual p is a one-dimensional array of array element spacing [d1, d2, d3, …, d N-1 ]; the population size NP represents the population [p1,p2,p3,…,p NP ], where each individual is a one-dimensional array with a dimension of N-1, representing the N-1 array element spacings of the N-element optical phased array; substituting the above data into the far-field light intensity distribution expression, the light intensity distribution of the phased array at each angle within the preset scanning range can be obtained, and the sidelobe suppression ratio of the non-periodic phased array at different deflection angles within the predetermined scanning range under this spacing can be calculated. The affinity function F in this embodiment is set to the grating lobe suppression ratio at the maximum deflection angle within the global scanning range, so as to ensure the lowest sidelobe level within the entire steering range.

[0034] Step 4: The optimal channel spacing is obtained by using the immune optimization algorithm, thereby obtaining the optimal transmission array, such as Figure 2 As shown, the following steps are included:

[0035] Identify antigens and create an initial population, that is, randomly initialize the values ​​of immune individuals within the channel interval.

[0036] Calculate the affinity function value of each immune individual, update the local best immune individual and the global best immune individual, that is, calculate the sidelobe suppression ratio of the non-periodic phased array at different deflection angles within the predetermined scanning range at the spacing, and obtain the grating lobe suppression ratio at the maximum deflection angle value within the global scanning range. Compare the obtained affinity function value with the local best immune individual Na and the global best immune individual Bestf. If it is better than the local best immune individual Na and the global best immune individual Bestf, the obtained affinity function value will replace the local best immune individual Na and the global best immune individual Bestf.

[0037] Determine whether the termination condition is met;

[0038] If it is not satisfied, immune individuals with affinity values ​​exceeding the threshold are selected for memory, and the suppression and promotion of immune individuals are performed;

[0039] Perform immune operations (including cloning, mutation, and clonal suppression) to update the population, and recalculate the affinity function value of each immune individual in the population until the termination condition is met. When the termination condition is met, the obtained global best immune individual Bestf is the optimal emission array. The termination condition in this embodiment is whether the current number of iterations reaches the set number of iterations.

[0040] It is not difficult to find that the present invention takes the array element factor into consideration during the immune optimization stage and substitutes it into the algorithm for optimization, and combines the influence of the main light beam being weakened by the directional factor when it is deflected in the actual scene. The obtained far-field light intensity distribution can better represent the actual scanning condition. The non-periodic optical phased array optimized by the algorithm has a low grating lobe suppression ratio within the set scanning range, and can increase the emission aperture and reduce the beam divergence angle.

Claims

1. An optimization method for non-uniform periodic arrangement of an optical phased array, characterized in that: The following steps are involved: Obtain the far-field light intensity distribution expression of the optical phased array; Setting a sequence formed by the spacings of the channels in the optical phased array as a vector to be optimized; The vector to be optimized is taken as an immune individual, and an immune optimization algorithm is used to solve and obtain the optimal spacing between each channel, so that the optical phased array has the lowest grating lobe suppression ratio within a preset scanning range.

2. The optimization method for non-equiperiodic arrangement of an optical phased array according to claim 1, characterized in that: The affinity function of the immune optimization algorithm is the grating lobe suppression ratio at the maximum deflection angle within the global scanning range.

3. The optimization method for non-equiperiodic arrangement of an optical phased array according to claim 1, characterized in that: The far-field light intensity distribution expression is: Wherein, E is the far-field light intensity distribution of the optical phased array, N is the number of array elements, and A is i is the amplitude strength of the i-th array element, f is the array element factor, x i is the position of the i-th array element, λ is the operating wavelength, θ s is the deflection angle, and θ is the field of view angle of the optical phased array scanning.

4. The optimization method for non-equiperiodic arrangement of an optical phased array according to claim 3, characterized in that: The grating lobe suppression ratio is calculated by using the far-field light intensity distribution expression.

5. The optimization method for non-equiperiodic arrangement of an optical phased array according to claim 1, characterized in that: The immune optimization algorithm is used to solve the optimal channel spacing, specifically: Set the population size, the dimension of immune individuals and the number of iterations; Identify antigens and create an initialized population; wherein each immune individual in the population is a sequence formed by the spacing of each channel in the optical phased array; Calculate the affinity function of each immune individual in the population, and update the local best immune individual and the global best immune individual; Determine whether the termination condition is met; If it is not satisfied, immune individuals with affinity values ​​exceeding the threshold are selected for memory, and the suppression and promotion of immune individuals are performed; Perform immune operations to update the population and recalculate the affinity function of each immune individual in the population until the termination condition is met.

6. The optimization method for non-equiperiodic arrangement of an optical phased array according to claim 5, characterized in that: The termination condition is whether the current number of iterations reaches the set number of iterations.

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