Laser terminal light spot energy optimization and troubleshooting method based on PSO algorithm

Abstract

The invention discloses a laser terminal light spot energy optimization and troubleshooting method based on a PSO algorithm, and the method comprises the steps: firstly initializing the position and speed of each particle in a particle swarm within a receiving range of a laser detector; for each particle, according to the current position of the particle, evaluating the light energy value of the current position of the particle; the light energy value of the current position of the particle is compared with the individual optimal value of the particle to update the individual optimal position; comparing the light energy value with a group optimal value, and updating a group optimal position; updating the speed and the position of each particle under the guidance of the individual optimal position and the group optimal position of the particle; and iterating the cycle process, finally obtaining the maximum value point of the light spot energy on the laser detector according to the final distribution position of the particle swarm, and judging whether the laser detector has a fault or not according to the number of the maximum value points.

Description

Technical Field

[0001] The present invention relates to the field of intersatellite link establishment and laser communication, and in particular to a laser terminal spot energy optimization and troubleshooting method based on a PSO algorithm. Background Art

[0002] With the continuous development of laser communication technology, intersatellite laser communication technology has become a hot spot for development. There are various tracking methods and means. The laser detectors used include focal plane detectors, QD detectors, PD detectors, COMS detectors, etc.

[0003] In the actual on-orbit link building process of the laser terminal, when the energy of the light spot on the detector is unstable, or there is a light cutting problem, resulting in multiple light spots on the detector, it will lead to the inability to achieve stable tracking. In severe cases, it may even cause abnormal noises in the mechanism, further damaging the mechanism. However, the traditional troubleshooting method is to connect the focal plane ground inspection, COMS ground inspection, etc., and then determine the problem by checking the light spot in the detector; however, this method is time-consuming and labor-intensive, the troubleshooting speed is extremely low, and when there is a problem with the ground inspection, it will bring certain difficulties to the problem troubleshooting; therefore, how to directly, quickly and accurately find the position and number of light spots on the detector, improve the speed of problem troubleshooting, and improve the stability of the on-orbit link building of the laser terminal has become an urgent problem to be solved. Summary of the invention

[0004] The technical problem solved by the present invention is: to overcome the shortcomings of the prior art and provide a method for optimizing the laser terminal spot energy and troubleshooting based on the PSO algorithm. By utilizing the advantages of the PSO algorithm, this optimization method is applied to the optimization and troubleshooting of the laser terminal light energy, thereby achieving a more autonomous, rapid and reliable troubleshooting method.

[0005] The technical solution of the present invention is: a laser terminal spot energy optimization and troubleshooting method based on the PSO algorithm, comprising the following steps:

[0006] S1, initialization: Initialize the position and velocity of each particle in the particle swarm within the receiving range of the laser detector;

[0007] S2. Evaluate particles: for each particle, evaluate the light energy value of the current position of the particle according to the current position of the particle;

[0008] S3, update the optimal position: for each particle, compare the light energy value of the current position of the particle with its individual optimal value. When the light energy value is greater than the individual optimal value, update the individual optimal position to the current position of the particle; compare the light energy value with the group optimal value. When the light energy value is greater than the group optimal value, update the group optimal position to the current position of the particle;

[0009] The individual optimal value is the maximum light energy value historically evaluated by the particle itself, and the individual optimal position is the position corresponding to the individual optimal value; the group optimal value is the maximum light energy value historically evaluated by all particles, and the group optimal position is the position corresponding to the group optimal value;

[0010] S4, update particle position: for each particle, under the guidance of its own individual optimal position and the group optimal position, update its respective speed and position;

[0011] S5, repeat S2 to S4 until the set stop condition is met, end the cycle, and obtain the maximum energy point of the spot on the laser detector according to the final distribution position of the particle group. One maximum point corresponds to one spot position;

[0012] S6. Determine whether the laser detector is faulty based on the number of maximum points.

[0013] Furthermore, each particle in the particle swarm is described by three D-dimensional vectors, and the three D-dimensional vectors of the i-th particle are expressed as:

[0014] Current location: x i =(x i1 ,x i2 ,,...,x iD );

[0015] Individual optimal position: p i =(p i1 ,p i2 ,,...,p iD );

[0016] Current speed: v i =(v i1 ,v i2 ,,...,v iD );

[0017] Where i = 1, 2, ..., n, n is the number of particles in the particle swarm, and D is the coordinate dimension describing the spatial point;

[0018] The entire particle swarm uses a D-dimensional vector to describe the optimal position of the swarm: p g =(p g1 ,p g2 ,,...,p gD );

[0019] For each particle, the d-th dimension velocity and position are updated as follows:

[0020] v id更新后 =v id更新前 +c1·rand()(p id -p iD)+c2·rand()·(p gd -p id )

[0021] x id更新后 =x id更新前 +v id更新后

[0022] Among them, d ranges from 1 to D, c1 and c2 are two non-negative constants, representing the particle's ability to summarize itself and its ability to learn from excellent individuals in the group, respectively; rand() is a random function with values ​​in the range [0 1].

[0023] Further, when the number of maximum points obtained is 1, it is determined that the laser detector has no fault; when the number of maximum points obtained is greater than 1, it is determined that the laser detector has a fault.

[0024] The present invention also provides a laser terminal spot energy optimization and troubleshooting system based on the PSO algorithm, comprising:

[0025] An initialization module is used to initialize the position and velocity of each particle in the particle swarm within the receiving range of the laser detector;

[0026] A particle evaluation module is used to evaluate the light energy value of each particle at its current position according to the particle's current position;

[0027] The optimal position updating module is used to compare the light energy value of the current position of each particle with its individual optimal value. When the light energy value is greater than the individual optimal value, the individual optimal position is updated to the current particle position; compare the light energy value with the group optimal value. When the light energy value is greater than the group optimal value, the group optimal position is updated to the current particle position; the individual optimal value is the maximum light energy value historically evaluated by the particle itself, and the individual optimal position is the position corresponding to the individual optimal value; the group optimal value is the maximum light energy value historically evaluated by all particles, and the group optimal position is the position corresponding to the group optimal value;

[0028] The particle position update module is used to update the speed and position of each particle under the guidance of its own individual optimal position and the group optimal position;

[0029] The loop control module is used to cyclically call the initialization module, the optimal position update module and the particle position update module under the set stop condition constraint; when the set stop condition is met, the loop process ends.

[0030] The fault judgment module is used to judge whether the laser detector has a fault according to the number of maximum points; the maximum point is obtained according to the particle group distribution position finally determined by the particle position update module, and one maximum point corresponds to one spot position.

[0031] Furthermore, the fault judgment method of the fault judgment module is: when the number of maximum value points obtained is 1, it is judged that the laser detector has no fault; when the number of maximum value points obtained is greater than 1, it is judged that the laser detector has a fault.

[0032] The present invention also provides a computer program product, which implements the steps of any of the methods described above when executed by a processor.

[0033] The present invention also provides an on-board computing terminal, including a terminal body and a controller, wherein the controller includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the functions of any of the above-described systems are realized.

[0034] The advantages of the present invention compared with the prior art are:

[0035] (1) Traditional laser terminal detector problem troubleshooting is achieved through ground inspection and data leakage. Traditional troubleshooting methods have great uncertainty during on-orbit operation, and the amount of data is large, making it difficult to troubleshoot detector problems, especially for multi-array detectors such as planar array detectors. The amount of data is large and it is impossible to achieve real-time data leakage, making it difficult to locate the problem, which in turn affects the efficiency of problem location. The present invention innovatively proposes an optimized detection scheme based on the PSO algorithm. For the on-orbit link establishment process of the laser terminal, it can directly and effectively determine the spot energy state and troubleshoot detector problems on-orbit, with higher efficiency and better troubleshooting methods.

[0036] (2) The method proposed in the present invention can quickly locate the energy state of the light spot, the detection state of the detector and other related variable states. The 1553 bus, CAN bus, 422 bus and other communication transmission methods can be used to quickly transmit data on orbit, and the light spot state can be directly returned to the ground, so as to efficiently formulate the next step of troubleshooting plan, which is of great significance to the on-orbit operation of the laser terminal and the on-orbit link establishment. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a flow chart for implementing the PSO algorithm of the present invention;

[0038] Figure 2 A comparison diagram of three-dimensional optimization effects of different iteration times and a two-dimensional curve diagram of the results after iteration in an embodiment of the present invention;

[0039] Figure 3 A comparison diagram of three-dimensional optimization effects of different iteration times and a two-dimensional curve diagram of the results after iteration in an embodiment of the present invention;

[0040] Figure 4This is a schematic diagram of the optimization result of the three-dimensional curve of the irregular shape of the light spot in an embodiment of the present invention;

[0041] Figure 5 A schematic diagram of a three-dimensional curve optimization result for simulating a light spot shape in an embodiment of the present invention;

[0042] Figure 6 It is a schematic diagram of the three-dimensional curve optimization result under the condition of poor spot image quality in an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to better understand the technical solution of the present invention, the embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0044] The laser terminal spot energy optimization and troubleshooting method based on the PSO algorithm proposed in the present invention includes the following steps, wherein the PSO algorithm implementation process is as follows: Figure 1 As shown:

[0045] Step 1: Initialization: Initialize the position and velocity of each particle in the particle swarm within the receiving range of the laser detector.

[0046] The specific initialization parameters in this embodiment are shown in the following table:

[0047]

[0048] Step 2: Evaluate particles: For each particle, based on the current position of the particle, evaluate the applicable value of the D-dimensional optimization function, that is, the light energy value at the current position of the particle.

[0049] Step 3: Update the optimal position: For each particle, compare the light energy value of the particle's current position with its individual optimal value. When the light energy value is greater than the individual optimal value, update the individual optimal position to the current particle position; compare the light energy value with the group optimal value. When the light energy value is greater than the group optimal value, update the group optimal position to the current particle position.

[0050] Among them, the individual optimal value is the maximum light energy value historically evaluated by the particle itself, and the individual optimal position is the position corresponding to the individual optimal value; the group optimal value is the maximum light energy value historically evaluated by all particles, and the group optimal position is the position corresponding to the group optimal value.

[0051] Specifically, the particle swarm optimization (PSO) algorithm is mathematically described as follows:

[0052] A group of n particles flies at a certain speed in the D-dimensional search space. When searching, each particle takes into account the historical best point it has searched and the historical best points of other particles in the group (or neighborhood), and changes its position (the position is also the solution) on this basis.

[0053] The i-th particle of the particle swarm is composed of three D-dimensional vectors, whose three parts are:

[0054] Current location: x i =(x i1 ,x i2 ,,...,x iD )

[0055] Historical best position: p i =(p i1 ,p i2 ,,...,p iD )

[0056] Speed: v i =(v i1 ,v i2 ,,...,v iD )

[0057] Here i = 1, 2, ..., n. The current position is considered as a set of coordinates describing a point in space. In each iteration of the algorithm, the current position x i It is evaluated as a solution to the problem. If the current position is better than the historical optimal position (i.e., the individual optimal position) p i , then the coordinates of the current position have a second historical optimal position p i .

[0058] In addition, the best position searched so far in the entire particle swarm (i.e., the optimal position of the group) is recorded as: p g =(p g1 ,p g2 ,,...,p gD ).

[0059] Step 4: Update particle position: For each particle, update its speed and position under the guidance of its own individual optimal position and the group optimal position.

[0060] Specifically, for each particle, its dth dimension (1≤d≤D) changes according to the following equation:

[0061] v id更新后 =v id更新前 +c1·rand()(p id -p iD )+c2·rand()·(p gd -p id )

[0062] x id更新后 =x id更新前 +v id更新后

[0063] The acceleration constants c1 and c2 are two non-negative values. These two constants enable particles to summarize themselves and learn from excellent individuals in the group, so as to approach their own historical optimal point and the global optimal point in the group or field. c1 and c2 are preferably 2. rand() is a random function with values ​​in the range [0 1].

[0064] Step 5: Repeat steps 2 to 4 until the set stop condition is met (usually the best applicability value and the maximum number of iterations), end the loop process, and obtain the maximum energy point of the spot on the laser detector according to the final distribution position of the particle swarm. One maximum point corresponds to one spot position.

[0065] Step 6: Determine whether the laser detector is faulty based on the number of maximum points.

[0066] Specifically, when the number of maximum value points obtained is 1, it is determined that the laser detector has no fault; when the number of maximum value points obtained is greater than 1, it is determined that the laser detector has a fault.

[0067] The present invention also provides a laser terminal spot energy optimization and troubleshooting system based on the PSO algorithm, and utilizes the aforementioned method to realize the functions of each module in the system.

[0068] The following are simulation results of optimizing the method of the present invention for several light spot situations to illustrate the effectiveness of the method.

[0069] like Figure 2 As shown, it is a comparison diagram of the three-dimensional optimization effect of different iteration times in the method of the present invention, and a schematic diagram of the two-dimensional curve of the result after iteration. Through comparative analysis, it can be seen that the greater the number of iterations, the better the optimization effect, and the more likely it is to achieve the ideal vertex position.

[0070] like Figure 3 As shown, it is a comparison diagram of the three-dimensional optimization effect of different iteration times in the method of the present invention, and a schematic diagram of the two-dimensional curve of the result after iteration. Through comparative analysis, it can be seen that when faced with extreme points and maximum points, the method of the present invention also has the optimization ability and can find the global optimum through continuous iteration.

[0071] like Figure 4 As shown, it is a schematic diagram of the optimization result of the three-dimensional curve of the irregular shape of the light spot. It can be seen from the observation that with the continuous increase in the number of iterations, the fitness value also decreases. When faced with the working conditions of irregular objective functions, the method of the present invention can find the optimal value, even if there are situations where the optimal values ​​are relatively similar.

[0072] like Figure 5As shown in the figure, it is a schematic diagram of the optimization result of the three-dimensional curve simulating the spot shape. Through analysis, it can be seen that the three simulations represent the comparison of one simulation, 20 simulations, and 50 simulation results respectively; through analysis, it can be seen that in the case of simulating the actual spot, the optimization effect is significant, and the fitness value is slightly different each time, but it does not affect the final result.

[0073] like Figure 6 As shown, it is a schematic diagram of the three-dimensional curve optimization result when the light spot image quality is poor. The distribution of the light spot at the top has certain irregularity. Under this condition, the method of the present invention can find the best position, and the process is not affected by the light energy distribution.

[0074] From the above analysis, it can be seen that the application of the method of the present invention in the field of laser terminals will greatly improve the speed of troubleshooting, especially when applied to focal plane detectors and COMS detectors, it can effectively reduce the dependence on focal plane ground detection and COMS ground detection, and avoid the problem that problems cannot be troubleshooted when ground detection equipment cannot be used.

[0075] It is to be understood that the present invention is described by way of embodiments, and it is known to those skilled in the art that various changes or equivalent substitutions may be made to these features and embodiments without departing from the spirit and scope of the present invention. In addition, under the teachings of the present invention, these features and embodiments may be modified to adapt to specific circumstances without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed herein, and embodiments that can fall within the scope of the claims of this application all fall within the scope protected by the present invention.

[0076] The contents not described in detail in the specification of the present invention belong to the common knowledge of those skilled in the art.

Claims

1. A laser terminal spot energy optimization and troubleshooting method based on PSO algorithm, characterized in that: The steps include: S1, initialization: Initialize the position and velocity of each particle in the particle swarm within the receiving range of the laser detector; S2. Evaluate particles: for each particle, evaluate the light energy value of the current position of the particle according to the current position of the particle; S3, update the optimal position: for each particle, compare the light energy value of the current position of the particle with its individual optimal value. When the light energy value is greater than the individual optimal value, update the individual optimal position to the current position of the particle; compare the light energy value with the group optimal value. When the light energy value is greater than the group optimal value, update the group optimal position to the current position of the particle; The individual optimal value is the maximum light energy value historically evaluated by the particle itself, and the individual optimal position is the position corresponding to the individual optimal value; the group optimal value is the maximum light energy value historically evaluated by all particles, and the group optimal position is the position corresponding to the group optimal value; S4, update particle position: for each particle, under the guidance of its own individual optimal position and the group optimal position, update its respective speed and position; S5, repeat S2 to S4 until the set stop condition is met, and the cycle ends. The maximum energy point of the light spot on the laser detector is obtained according to the final distribution position of the particle group. One maximum point corresponds to one light spot position. S6. Determine whether the laser detector is faulty based on the number of maximum points.

2. The laser terminal spot energy optimization and troubleshooting method based on the PSO algorithm according to claim 1 is characterized by: Each particle in the particle swarm is described by three D-dimensional vectors. The three D-dimensional vectors of the i-th particle are expressed as: Current location: x i =(x i1 ,x i2 ,,...,x iD ); Individual optimal position: p i =(p i1 ,p i2 ,,...,p iD ); Current speed: v i =(v i1 ,v i2 ,,...,v iD ); Where i = 1, 2, ..., n, n is the number of particles in the particle swarm, and D is the coordinate dimension describing the spatial point; The entire particle swarm uses a D-dimensional vector to describe the optimal position of the swarm: p g =(p g1 ,p g2 ,,...,p gD ); For each particle, the d-th dimension velocity and position are updated as follows: v id更新后 =v id更新前 +c1·rand()·(p id -p iD )+c2·rand()·(p gd -p id ) x id更新后 =x id更新前 +v id更新后 Among them, d ranges from 1 to D, c1 and c2 are two non-negative constants, representing the particle's ability to summarize itself and its ability to learn from excellent individuals in the group, respectively; rand() is a random function with values ​​in the range [0 1].

3. The laser terminal spot energy optimization and troubleshooting method based on the PSO algorithm according to claim 1 is characterized by: When the number of maximum points obtained is 1, it is judged that the laser detector has no fault; when the number of maximum points obtained is greater than 1, it is judged that the laser detector has a fault.

4. A laser terminal spot energy optimization and troubleshooting system based on PSO algorithm, characterized in that: include: An initialization module is used to initialize the position and velocity of each particle in the particle swarm within the receiving range of the laser detector; A particle evaluation module is used to evaluate the light energy value of each particle at its current position according to the particle's current position; The optimal position updating module is used to compare the light energy value of the current position of each particle with its individual optimal value. When the light energy value is greater than the individual optimal value, the individual optimal position is updated to the current particle position; compare the light energy value with the group optimal value. When the light energy value is greater than the group optimal value, the group optimal position is updated to the current particle position; the individual optimal value is the maximum light energy value historically evaluated by the particle itself, and the individual optimal position is the position corresponding to the individual optimal value; the group optimal value is the maximum light energy value historically evaluated by all particles, and the group optimal position is the position corresponding to the group optimal value; The particle position update module is used to update the speed and position of each particle under the guidance of its own individual optimal position and the group optimal position; The loop control module is used to cyclically call the initialization module, the optimal position update module and the particle position update module under the set stop condition constraint; when the set stop condition is met, the loop process ends. The fault judgment module is used to judge whether the laser detector has a fault according to the number of maximum points; the maximum point is obtained according to the particle group distribution position finally determined by the particle position update module, and one maximum point corresponds to one spot position.

5. The laser terminal spot energy optimization and troubleshooting system based on the PSO algorithm according to claim 4 is characterized by: The fault judgment method of the fault judgment module is: when the number of maximum value points obtained is 1, it is judged that the laser detector has no fault; when the number of maximum value points obtained is greater than 1, it is judged that the laser detector has a fault.

6. A computer program product, characterized in that: When the computer program product is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

7. An on-board computing terminal, comprising a terminal body and a controller, characterized in that: The controller includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the functions of the system as claimed in any one of claims 4 to 5 are realized.

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