Efficient communication resource allocation method for low-orbit communication satellites

Abstract

The invention belongs to the technical field of satellite communication, and discloses a high-efficiency communication resource allocation method for a low-orbit communication satellite, which comprises the following steps of: (1) arranging a ground wave position according to a satellite height and a coverage area; (2) estimating the satellite service time and the hopping beam period according to the satellite height and the service distance; (3) estimating time resources required by sensing according to the ground wave position distribution and the sensing target type; (4) estimating resources required by communication according to the geographic position and the development condition of the ground wave position; (5) for a specific scene, performing time slot allocation joint optimization according to perception and communication requirements; and (6) generating a hopping beam pattern according to communication and sensing characteristics by using a time slot allocation result. According to the invention, the sensing module is introduced, joint optimization is carried out on the hopping beam time slot distribution, the hopping beam pattern is generated, on the basis of not damaging the original communication system, the communication and sensing integrated design is realized, the system efficiency is maximized, and the method is more suitable for the communication and sensing scenes of future low-orbit satellites.

Description

Technical Field

[0001] The invention belongs to the technical field of satellite communications, and in particular relates to a high-efficiency synaesthesia resource allocation method for a low-orbit communication satellite. Background Art

[0002] Synaesthesia, or communication and perception integration, is one of the important new capabilities and innovative directions for future communications. By integrating communication and perception systems, this technology has the characteristics of multi-sensory, natural, interactive and intelligent, and has broad application prospects in low-altitude economy, smart transportation, smart manufacturing and other fields.

[0003] The current synaesthesia integrated platform is commonly found in ground base stations and drones, with limited coverage and limited sensing targets. Compared with the ground terminal, the low-orbit satellite platform has huge advantages in operating costs, coverage, working capacity, anti-interference ability, etc., and is an excellent carrier for synaesthesia integration.

[0004] However, there are few studies on interawareness integration based on low-orbit satellites, especially in terms of demand analysis, system design and resource allocation on the communication and perception side. Existing satellite perception technology is common in space-based early warning satellites, which directly use the working mechanism of ground radars, have high power, high cost, obvious targets, and use scenarios that are out of the scope of civil use. Existing literature proposes to use low-orbit communication satellites to complete perception tasks. They have low orbit altitudes, high ground receiving power, large numbers, and wide coverage areas. Compared with high-orbit satellites, they have a higher possibility of achieving perception. However, their functional design is completely based on existing radar perception, sacrificing all communication capabilities to complete perception, and failing to consider the actual working needs and characteristics of communication satellites, which is unrealistic for civil communication satellites.

[0005] In order to utilize limited platform resources, existing satellite communications often use a beam hopping mechanism, which achieves coverage of more areas by utilizing beam hopping between different wave positions, maximizing the utilization of system resources. Under this system, the resource allocation system is relatively complete, with the goal of maximizing user satisfaction. However, under this system, resource allocation is entirely based on communication considerations, leaving no spare resources for the perception side, and lacks demand analysis at the perception level, making it impossible to directly be compatible with the perception module. Therefore, how to correctly estimate the perception requirements, realize synaesthesia joint design, and maximize system efficiency while being compatible with the existing satellite communication system is a problem that needs to be solved. Summary of the invention

[0006] In order to overcome the shortcomings of the prior art, the present invention introduces perception demand analysis and joint optimization design, and proposes an efficient synaesthesia resource allocation method for low-orbit communication satellites. Combined with the beam-hopping working system, when platform resources are limited and it is impossible to allocate spare perception resources, the synaesthesia time resource allocation is jointly optimized to generate a beam-hopping pattern, maximize the utilization of system resources, and realize synaesthesia integration.

[0007] In order to achieve the above object, the present invention is achieved through the following technical solutions:

[0008] The present invention is an efficient synaesthesia resource allocation method for a low-orbit communication satellite, and the synaesthesia resource allocation method specifically comprises the following steps:

[0009] Step 1: According to the satellite orbit height and beam width , estimate the radius of a single ground wave position , the size and shape of the cluster are obtained by expanding outward from the central wave position, and the ground wave position is arranged to obtain the ground wave position distribution;

[0010] Step 2: According to the satellite orbit height And the maximum service distance between satellite and ground , estimate the maximum service time of the satellite , determine the number of time slots in the beam hopping period and single slot length ;

[0011] Step 3: Use the ground wave position distribution obtained in step 1, combined with the perceived target type and radar link propagation equation, to estimate the perception requirement time for each ground wave position. ;

[0012] Step 4: Using the ground wave position distribution obtained in step 1, weight the ground wave position according to the geographical location. and economic weighting factors or vessel traffic weighting factor , estimate the communication resource requirements for each wave ;

[0013] Step 5: Use the perceived resource requirements obtained in step 3 The communication resource requirements obtained in step 4 , the time slot allocation is jointly optimized with the second-order difference function as the target to obtain the number of time slots required for each wave position ;

[0014] Step 6: Use the number of time slots required for each wave position obtained in step 5 , combined with the maximum holding time of the user terminal Maximum interruption time with target perception , determine the satellite beam’s dwell time and working order at each wave position, and generate a beam hopping pattern.

[0015] A further improvement of the present invention is that in step 1, performing ground wave position arrangement specifically includes the following steps:

[0016] Step 1.1: Obtain the ground wave radius covered by a single beam based on the satellite orbit height and beam width:

[0017]

[0018] in, is the working wavelength, is the antenna aperture, is the beam width, is the satellite orbit altitude, is the ground wave radius;

[0019] Step 1.2: Arrange the ground wave positions based on the design of a single ground wave position: the wave position shape is set to a regular hexagon, and the arrangement is expanded outward from the central wave position to form a cluster consisting of multiple wave positions. The wave positions are numbered separately to facilitate the analysis of the communication and perception requirements of each wave position. The ground wave position radius of the wave position The distance between adjacent wave position centers is ,The satellite coverage area is divided into a set of multiple clusters.,Since the resource scheduling method of each cluster is the same, the following demand analysis and,optimization process are all based on a single cluster and a single beam.

[0020] A further improvement of the present invention is that the step 2 specifically comprises the following steps:

[0021] Step 2.1, calculate the satellite's speed based on the satellite's altitude:

[0022]

[0023] in, is the satellite speed, is the gravitational constant, is the mass of the Earth, is the satellite orbit altitude, is the radius of the earth. The maximum receiving elevation angle between the satellite and the ground receiving end is set to 60°. When the curvature of the earth is not considered, the maximum satellite-to-ground service distance between the satellite and the ground receiving end is Approximately satellite orbit altitude twice, that is = ;

[0024] Step 2.2: Maximum service time of satellite The distance and speed of the satellite The distance from the satellite to the top is determined by the satellite orbital altitude , the radius of the Earth and the maximum satellite-to-ground service distance Sure:

[0025] θ r = a cos[( r e 2 + ( r e + h ) 2 − R max 2 ) / ( 2 × r e × ( r e + h ))]

[0026]

[0027]

[0028] in, It is the angle between the satellite and the earth's center when the satellite reaches the farthest serviceable segment. The overhead distance at which the satellite can provide service, is the maximum service time of the satellite. The beam hopping period length is less than the maximum service time and is set to an integer number of seconds. The number of beam hopping time slots is The length of a single time slot is obtained by determining the beam hopping period and the number of time slots. , single time slot length Equal to the beam hopping period length divided by the number of time slots .

[0029] A further improvement of the present invention is that the step 3 specifically includes the following steps:

[0030] Step 3.1: The distance between the centers of adjacent wave positions and the satellite's orbital altitude Get the distance between the satellite and each ground wave center , assuming that the initial position of the satellite is directly above the cluster center wave position, then the distance between the satellite and the wave position center is , the distances between other wave position centers and satellites are obtained by the satellite height and the number of adjacent wave position intervals. ,in, is the number of wave positions between this wave position and the central wave position;

[0031] Step 3.2: According to the distance between the satellite and the ground wave position center Calculate the perceived demand time in static scenarios and the perceived demand time in dynamic service scenarios .

[0032] A further improvement of the present invention is that in a static scenario, the link propagation equation of the radar is:

[0033]

[0034] in, is the maximum transmit power, is the transmit gain, is the transmit aperture, To perceive the target size, is the equivalent accumulated pulse number, is the pulse accumulation efficiency, is the Boltzmann constant, is the noise temperature, is the noise factor, is the noise bandwidth, The maximum sensing distance.

[0035] is the signal-to-noise ratio required for single pulse detection, given by the false alarm probability and the detection probability get:

[0036] ( S / N ) 1 = A + 0 . 12 AB + 1 . 7 B A = ln[ 0 . 62 / P fa ] B = ln[ P d / ( 1 − P d )]

[0037] is the average transmission power, which is determined by the maximum peak power Convert to:

[0038]

[0039] in, is the pulse duration, is the pulse width. Use the receiver half-power bandwidth Noise bandwidth , peak power Convert to average power , half-power bandwidth and pulse width The product of the two In a simple unmodulated pulse radar system, it is equal to 1, and finally we can get The time required for perception is:

[0040]

[0041] in, For receiving gain.

[0042] A further improvement of the present invention is that in a dynamic service scenario, based on determining the initial position and movement direction of the satellite, the distance between satellite targets is related to the satellite movement time during the sensing process. Assuming that the sensing target is stationary at the center of the wave position, the initial position of the satellite is directly above the center of the wave position, and the movement direction is away from the center of the wave position, the distance between the satellite and the center of the wave position can be expressed as:

[0043]

[0044] in, is the satellite motion time, It is the distance between the satellite and the ground wave center, i.e. the target.

[0045] The entire continuous perception process in a dynamic scene can be regarded as the accumulation of the accumulated signal-to-noise ratio. The satellite's motion trajectory is divided into arcs of equal length. When the arcs are small enough, it can be considered that the perception distance between the satellite and the target is the same during this motion, and the accumulated signal-to-noise ratio in each period of time is calculated.

[0046] By calculating the accumulated signal-to-noise ratio until the minimum signal-to-noise ratio required for perception is met, the time required to complete the perception task can be obtained:

[0047]

[0048] In the formula, It is The accumulated signal-to-noise ratio within the segment arc, It is The time of the arc movement, It is The distance of the satellite target within the arc segment, thus obtaining the satellite's perception requirement time .

[0049] A further improvement of the present invention is that: in step 4, each ground wave position is divided into grids based on longitude and latitude, and the communication resource demand of the ground wave position is determined by calculating the sum of the traffic volume of all grids. , specifically including:

[0050] Step 4.1: The weighting factor for the geographical location of land is , using the gross regional product per unit area To measure the economic development of a region, the economic weighting factor The calculation formula is as follows:

[0051]

[0052]

[0053] in, is the total area of ​​the grid value, is the size of the grid, is the maximum regional GDP per unit area in all grids;

[0054] Step 4.2: The geographical location weighting factor of the ocean or lake is: The ship flow weighting factor is used to measure the flow difference between each grid:

[0055]

[0056] in, is the number of ships in the grid obtained by querying AIS ship positioning, is the maximum number of ships in all grids, and the traffic intensity factor of each grid It is expressed as:

[0057]

[0058] Step 4.3: Combine the basic communication rate of the area , the grid traffic intensity within the ground wave position is counted to obtain the communication traffic demand of the ground wave position :

[0059] .

[0060] A further improvement of the present invention is that the step 5 specifically includes the following steps:

[0061] Step 5.1, choose to use the interawareness integrated time slot to realize the reuse of time slot resources within the beam hopping period to achieve basic interawareness function. In order to ensure basic communication capabilities, choose to use the second-order difference objective function as the optimization target:

[0062]

[0063] in, It is The communication traffic provided by each wave bit is It is The communication traffic required for each wave position is is the number of wave positions in the cluster;

[0064] Step 5.2: After the optimization target is determined, the time slot joint optimization must meet the following constraints:

[0065] a. Communication constraints:

[0066]

[0067] in, To meet the needs of both communication and perception, For the wave position that only needs communication, It is The number of time slots allocated to each wave position, is the total number of time slots in the beam hopping period, is the maximum number of beams that can operate simultaneously in the cluster;

[0068] The amount of communication traffic provided by the beam With the number of time slots The relationship is:

[0069]

[0070] in, represents the communication loss coefficient, Total communication capacity provided for the synaesthesia integration system;

[0071] b. Perception constraints:

[0072]

[0073] in, is the perceived performance loss coefficient, is the length of a single time slot, The shortest required perception time is equal to the perception demand time ;

[0074] Step 5.3: Convert the second-order difference function optimization under constraints in step 5.1 into a convex optimization problem, and use the convex optimization toolbox to solve the integer solution for time slot allocation. .

[0075] A further improvement of the present invention is that the step 6 specifically comprises the following steps:

[0076] The integer solutions of the time slot allocation of each wave position obtained in step 5 are arranged in order of the number of time slots from small to large, so that the wave position with the small number of time slots is allocated first;

[0077] Step 6.2: Consider all the beam positions and ensure that all the beam positions have appeared within the maximum synchronization retention time of the communication user terminal, except for the allocated beam positions. Move the beam position time slots that have not appeared to the front to make the beam revisit time The maximum time to keep synchronization with the communication user terminal user Between, satisfy ;

[0078] Step 6.3: Consider a single beam position. The intervals of all time slots of the beam position cannot exceed the maximum interruption time of target perception. The time slots exceeding the maximum interruption time are moved to the front to make the beam revisit time Maximum interruption time with target perception ,satisfy ;

[0079] Step 6.4: After the time slot number arrangement in step 6.1 and the time slot shifting in steps 6.2 and 6.3, a beam hopping pattern is obtained.

[0080] The beneficial effects of the present invention are:

[0081] The present invention introduces the concept of synaesthesia integrated time slot, which can still provide basic perception resources for the target when the satellite platform resources are limited and no spare resources can be allocated, so that synaesthesia integrated transmission in the low-orbit satellite scenario can be realized.

[0082] The present invention utilizes the joint optimization of synaesthesia time slot allocation and the integrated design of beam hopping patterns to make it compatible with the existing beam hopping communication system and maximize the use of existing platform resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 The present invention is a flowchart of the synaesthesia resource optimization allocation process of the method of the present invention.

[0084] Figure 2 It is a schematic diagram of ground wave position arrangement in the present invention.

[0085] Figure 3 It is the time slot allocation result after joint optimization by the method of the present invention.

[0086] Figure 4 It is an integrated beam hopping pattern obtained by the method of the present invention. DETAILED DESCRIPTION

[0087] The following will disclose the embodiments of the present invention with drawings. For the purpose of clear description, many practical details will be described together in the following description. However, it should be understood that these practical details should not be used to limit the present invention. That is to say, in some embodiments of the present invention, these practical details are not necessary.

[0088] like Figure 1 As shown, the present invention is an efficient synaesthesia resource allocation method for a low-orbit communication satellite, and the synaesthesia resource allocation method specifically includes the following steps:

[0089] Step 1: According to the satellite orbit height and beam width , estimate the radius of a single ground wave position , the size and shape of the cluster are obtained by expanding outward from the wave position center, and the ground wave position is arranged to obtain the ground wave position distribution.

[0090] The ground wave position arrangement specifically includes the following steps:

[0091] Step 1.1: Obtain the ground wave radius covered by a single beam based on the satellite orbit height and beam width:

[0092]

[0093] in, is the working wavelength, is the antenna aperture, is the beam width, is the satellite orbit altitude, is the ground wave radius;

[0094] Step 1.2: Arrange the ground wave position based on the single ground wave design: the wave position shape is set to a regular hexagon, and a cluster of 7 wave positions is arranged from the central wave position outward, numbered 1 to 7, and the ground wave position radius of the wave position is The distance between adjacent wave position centers is ,The satellite coverage area is divided into a set of multiple clusters. Since the resource scheduling method of each cluster is the same, the following demand analysis and optimization process are all based on a single cluster and a single beam.

[0095] Step 2: According to the satellite orbit height And the maximum service distance between satellite and ground , estimate the maximum service time of the satellite , determine the number of time slots in the beam hopping period and single slot length , specifically including the following steps:

[0096] Step 2.1, calculate the satellite's speed based on the satellite's altitude:

[0097]

[0098] in, is the satellite speed, is the gravitational constant, is the mass of the Earth, is the satellite orbit altitude, is the radius of the earth. The maximum receiving elevation angle between the satellite and the ground receiving end is set to 60°. When the curvature of the earth is not considered, the maximum satellite-to-ground service distance between the satellite and the ground receiving end is Approximately satellite orbit altitude twice, that is = ;

[0099] Step 2.2: Maximum service time of satellite The distance and speed of the satellite The distance from the satellite to the top is determined by the satellite orbital altitude , the radius of the Earth and the maximum satellite-to-ground service distance Sure:

[0100] θ r = a cos[( r e 2 + ( r e + h ) 2 − R max 2 ) / ( 2 × r e × ( r e + h ))]

[0101]

[0102]

[0103] in, It is the angle between the satellite and the earth's center when the satellite reaches the farthest serviceable segment. The overhead distance at which the satellite can provide service, is the maximum service time of the satellite. The beam hopping period length is less than the maximum service time and is set to an integer number of seconds. The number of beam hopping time slots is The length of a single time slot is obtained by determining the beam hopping period and the number of time slots. , single time slot length Equal to the beam hopping period length divided by the number of time slots .

[0104] Step 3: Use the ground wave position distribution obtained in step 1, combined with the sensing target type and radar link propagation equation, to estimate the sensing time required for each ground wave position. , including the following steps:

[0105] Step 3.1: The distance between the centers of adjacent wave positions and the satellite's orbital altitude Get the distance between the satellite and each ground wave center , assuming that the initial position of the satellite is directly above the cluster center wave position, then the distance between the satellite and the wave position center is , the distances between other wave position centers and satellites are obtained by the satellite height and the number of adjacent wave position intervals. ,in, is the number of wave positions between the wave position and the center wave position. In this embodiment, the distance between the wave position No. 1 in the cluster and the satellite is: , the distances between the wave centers of clusters 2 to 7 and the satellite are the same: .

[0106] Step 3.2: According to the distance between the satellite and the ground wave position center Calculate the perceived demand time in static scenarios and the perceived demand time in dynamic service scenarios .

[0107] In a static scenario, the link propagation equation perceived by the radar is:

[0108]

[0109] in, is the maximum transmit power, is the transmit gain, is the transmit aperture, To perceive the target size, is the equivalent accumulated pulse number, is the pulse accumulation efficiency, is the Boltzmann constant, is the noise temperature, is the noise factor, is the noise bandwidth, The maximum sensing distance.

[0110] is the signal-to-noise ratio required for single pulse detection, given by the false alarm probability and the detection probability get:

[0111] ( S / N ) 1 = A + 0 . 12 AB + 1 . 7 B A = ln[ 0 . 62 / P fa ] B = ln[ P d / ( 1 − P d )]

[0112] is the average transmission power, which is determined by the maximum peak power Convert to:

[0113]

[0114] in, is the pulse duration, is the pulse width. Use the receiver half-power bandwidth Instead of noise bandwidth , peak power Convert to average power , half-power bandwidth and pulse width The product of the two In a simple unmodulated pulse radar system, it is equal to 1, and finally we can get The time required for perception is:

[0115]

[0116] in, For receiving gain.

[0117] In the dynamic service scenario, based on the initial position and movement direction of the satellite, the distance between satellite targets is related to the satellite movement time during the perception process. Assuming that the perception target is at the center of the wave position and does not move, the initial position of the satellite is directly above the wave position center, and the movement direction is away from the wave position center, the distance between the satellite and the wave position center can be expressed as:

[0118]

[0119] in, is the satellite motion time, It is the distance between the satellite and the ground wave position center, i.e. the target, during its motion;

[0120] The entire continuous perception process in a dynamic scene can be regarded as the accumulation of the accumulated signal-to-noise ratio. The satellite's motion trajectory is divided into arcs of equal length. When the arcs are small enough, it can be considered that the perception distance between the satellite and the target is the same during this motion, and the accumulated signal-to-noise ratio in each period of time is calculated.

[0121] By calculating the accumulated signal-to-noise ratio until the minimum signal-to-noise ratio required for perception is met, the time required to complete the perception task can be obtained:

[0122]

[0123] In the formula, It is The accumulated signal-to-noise ratio within the segment arc, It is The time of the satellite motion in this arc, It is The distance of the satellite target within the arc segment, thus obtaining the satellite's perception requirement time .

[0124] Step 4: Using the ground wave position distribution obtained in step 1, weight the ground wave position according to the geographical location. and economic weighting factors or vessel traffic weighting factor , estimate the communication resource requirements for each wave position .

[0125] In this step, each ground wave position is divided into grids based on longitude and latitude, and the communication resource requirements of the ground wave position are determined by calculating the sum of the traffic of all grids. , specifically including:

[0126] Step 4.1: The weighting factor for the geographical location of land is Set to 0.9, using the gross regional product per unit area To measure the economic development of a region, the economic weighting factor The calculation formula is as follows:

[0127]

[0128]

[0129] in, is the total area of ​​the grid value, is the size of the grid, is the maximum regional GDP per unit area in all grids;

[0130] Step 4.2: The weighting factor for the geographical location of an ocean or lake is Set to 0.1 to use the ship traffic weighting factor To measure the traffic differences between grids:

[0131]

[0132] in, is the number of ships in the grid obtained by querying AIS ship positioning, is the maximum number of ships in all grids, and the traffic intensity factor of each grid It is expressed as:

[0133]

[0134] Step 4.3: Combine the basic communication rate of the area , the grid traffic intensity within the ground wave position is counted to obtain the communication traffic demand of the ground wave position :

[0135] .

[0136] The communication capacity that the system can provide is determined by the beam itself. The total communication capacity within the cluster is:

[0137]

[0138] in, is the full frequency multiplexing bandwidth, is the signal-to-interference-noise ratio of the wave position, is the attenuation factor, is the equivalent downlink power, is the noise power, is the interference power. Here, only one beam is working in a single cluster and the interference power can be set to 0.

[0139] The equivalent downlink power is the receiving power of the ground terminal for:

[0140]

[0141] in In calculations, this is equal to the satellite altitude .

[0142] Step 5: Use the perceived needs obtained in step 3 The communication resource requirements obtained in step 4 , the time slot allocation is jointly optimized with the second-order difference function as the target to obtain the number of time slots required for each wave position .

[0143] The specific steps include:

[0144] Step 5.1, choose to use the interawareness integrated time slot to realize the reuse of time slot resources within the beam hopping period to achieve basic interawareness function. In order to ensure basic communication capabilities, choose to use the second-order difference objective function as the optimization target:

[0145]

[0146] in, It is The communication traffic provided by each wave bit is It is The communication traffic required for each wave position is is the number of wave positions in the cluster;

[0147] Step 5.2: After the optimization target is determined, the time slot joint optimization must meet the following constraints:

[0148] a. Communication constraints:

[0149]

[0150] in, To meet the needs of both communication and perception, For the wave position that only needs communication, It is The number of time slots allocated to each wave position, is the total number of time slots in the beam hopping period, is the maximum number of beams operating simultaneously in the cluster;

[0151] The amount of communication traffic provided by the beam With the number of time slots The relationship is:

[0152]

[0153] in, represents the communication loss coefficient, Total communication capacity provided for the synaesthesia integration system;

[0154] b. Perception constraints:

[0155]

[0156] in, is the perceived performance loss coefficient, is the length of a single time slot, The shortest required perception time is equal to the perception demand time ;

[0157] Step 5.3: Convert the second-order difference function optimization under constraints in step 5.1 into a convex optimization problem, and use the convex optimization toolbox to solve the integer solution for time slot allocation. .

[0158] Step 6: Use the number of time slots required for each wave position obtained in step 5 , combined with the maximum holding time of the user terminal Maximum interruption time with target perception , determine the dwell time and working order of the satellite beam at each wave position, and generate a beam hopping pattern, which specifically includes the following steps:

[0159] The integer solutions of the time slot allocation of each wave position obtained in step 5 are arranged in order of the number of time slots from small to large, so that the wave position with the small number of time slots is allocated first;

[0160] Step 6.2: Consider all the beam positions and ensure that all the beam positions have appeared within the maximum synchronization retention time of the communication user terminal, except for the allocated beam positions. Move the beam position time slots that have not appeared to the front to make the beam revisit time The maximum time to keep synchronization with the communication user terminal user Between, satisfy ;

[0161] Step 6.3: Consider a single beam position. The intervals of all time slots of the beam position cannot exceed the maximum interruption time of target perception. The time slots exceeding the maximum interruption time are moved to the front to make the beam revisit time Maximum interruption time with target perception ,satisfy ;

[0162] Step 6.4: After the time slot number arrangement in step 6.1 and the time slot shifting in steps 6.2 and 6.3, a beam hopping pattern is obtained.

[0163] In order to verify the beneficial effects of the present invention, the present invention provides a simulation experiment to further verify the present invention.

[0164] 1. Experimental scenario:

[0165] The scene is set to a common low-orbit communication satellite. The specific satellite parameters are: altitude 500km, operating frequency 6GHz, beam width 10.83 degrees, transmission power 80W, transmission gain 23.3dB, and bandwidth 40MHz.

[0166] 2. Experimental content and results:

[0167] Experiment 1: Arrange ground beam positions according to satellite conditions. According to the satellite altitude and beam width, estimate the radius of a single ground beam position, expand it to get the size and shape of the cluster, and arrange the ground beam positions. The results are as follows: Figure 2 shown.

[0168] Experiment 2: Jointly optimize time slot allocation based on demand and design beam hopping pattern. Figure 3 Comparison between conventional beam-hopping time slot allocation and time slot allocation after joint optimization. Figure 4 The beam-hopping pattern is designed to take into account the characteristics of synaesthesia. Figure 3 It can be seen that joint optimization can compensate a certain time slot for the presence sensing demand wave position, so that it can complete the sensing while ensuring the original communication function. Compared with the existing solution, the proposed solution can reasonably balance the system resources. Figure 4 It can be seen that the generated beam-hopping pattern can meet both communication needs and perception needs, and achieves compatibility with the conventional beam-hopping system.

[0169] The above description is only an embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.

Claims

1. An efficient synaesthesia resource allocation method for a low-orbit communication satellite, characterized in that: The synaesthesia resource allocation method specifically comprises the following steps: Step 1: According to the satellite orbit height and beam width , estimate the radius of a single ground wave position , the size and shape of the cluster are obtained by expanding outward from the central wave position, and the ground wave position is arranged to obtain the ground wave position distribution; Step 2: According to the satellite orbit height And the maximum service distance between satellite and ground , estimate the maximum service time of the satellite , determine the number of time slots in the beam hopping period and single slot length ; Step 3: Use the ground wave position distribution obtained in step 1, combined with the perceived target type and radar link propagation equation, to estimate the perception requirement time for each ground wave position. ; Step 4: Using the ground wave position distribution obtained in step 1, weight the ground wave position according to the geographical location. and economic weighting factors or vessel traffic weighting factor , estimate the communication resource requirements for each wave ; Step 5: Use the perceived resource requirements obtained in step 3 The communication resource requirements obtained in step 4 , the time slot allocation is jointly optimized with the second-order difference function as the target to obtain the number of time slots required for each wave position ; Step 6: Use the number of time slots required for each wave position obtained in step 5 , combined with the maximum holding time of the user terminal Maximum interruption time with target perception , determine the satellite beam’s dwell time and working order at each wave position, and generate a beam hopping pattern.

2. The method for efficiently allocating synaesthesia resources for a low-orbit communication satellite according to claim 1, characterized in that: In step 1, the ground wave position arrangement specifically includes the following steps: Step 1.1: Obtain the ground wave radius covered by a single beam based on the satellite orbit height and beam width: ， in, is the working wavelength, is the antenna aperture, is the beam width, is the satellite orbit altitude, is the ground wave radius; Step 1.2: Arrange the ground wave positions based on the design of a single ground wave position: the wave position shape is set to a regular hexagon, and the arrangement is expanded outward from the central wave position to form a cluster consisting of multiple wave positions. The wave positions are numbered separately to facilitate the analysis of the communication and perception requirements of each wave position. The ground wave position radius of the wave position The distance between adjacent wave position centers is ,The satellite coverage area is divided into a set of multiple clusters.

3. The method for efficiently allocating synaesthesia resources for a low-orbit communication satellite according to claim 1, characterized in that: The step 2 specifically includes the following steps: Step 2.1: Calculate the satellite's speed based on the satellite's orbital altitude: ， in, is the satellite speed, is the gravitational constant, is the mass of the Earth, is the satellite orbit altitude, is the radius of the earth. The maximum receiving elevation angle between the satellite and the ground receiving end is set to 60°. When the curvature of the earth is not considered, the maximum satellite-to-ground service distance between the satellite and the ground receiving end is Approximately satellite orbit altitude twice, that is = ; Step 2.2: Maximum service time of satellite The distance and speed of the satellite Confirmed, satellite overhead distance Satellite orbit height , the radius of the Earth and the maximum satellite-to-ground service distance Sure: ， ， in, It is the angle between the satellite and the ground receiving end when the satellite moves to the farthest serviceable segment. The overhead distance at which the satellite can provide service, is the maximum service time of the satellite. The beam hopping period length should be less than the maximum service time and set to an integer number of seconds. 128 or 64, single slot length Equal to the beam hopping period length divided by the number of time slots .

4. The method for efficiently allocating synaesthesia resources for a low-orbit communication satellite according to claim 1, characterized in that: The step 3 specifically comprises the following steps: Step 3.1: The distance between the centers of adjacent wave positions and the satellite's orbital altitude Get the distance between the satellite and each ground wave center , assuming that the initial position of the satellite is directly above the cluster center wave position, then the distance between the satellite and the wave position center is , the distances between other wave position centers and satellites are obtained by the satellite height and the number of adjacent wave position intervals. ,in, is the number of wave positions between this wave position and the central wave position; Step 3.2: According to the distance between the satellite and the ground wave position center Calculate the perceived demand time in static scenarios and the perceived demand time in dynamic scenarios .

5. The method for efficiently allocating synaesthesia resources for a low-orbit communication satellite according to claim 4, characterized in that: In a static scenario, the radar link propagation equation is: ， in, is the maximum transmit power, is the transmit gain, is the transmit aperture, To perceive the target size, is the equivalent accumulated pulse number, is the pulse accumulation efficiency, is the Boltzmann constant, is the noise temperature, is the noise factor, is the noise bandwidth, is the maximum sensing distance, is the signal-to-noise ratio required for single pulse detection, given by the false alarm probability and the detection probability get: ， is the average transmission power, which is determined by the maximum peak power Convert to: ， in, is the pulse duration, is the pulse width, using the receiver half-power bandwidth Noise bandwidth , peak power Convert to average power , half-power bandwidth and pulse width The product of the two In a simple unmodulated pulse radar system, it is equal to 1, and finally we get The time required for static perception is: ， in, For receiving gain.

6. The method for efficiently allocating synaesthesia resources for a low-orbit communication satellite according to claim 5, characterized in that: In the dynamic service scenario, based on the initial position and movement direction of the satellite, the distance between satellite targets is related to the satellite movement time during the perception process. Assuming that the perception target is stationary at the center of the wave position, the initial position of the satellite is directly above the center of the wave position, and the movement direction is away from the center of the wave position, the distance between the satellite and the center of the wave position can be expressed as: ， in, is the satellite motion time, It is the distance between the satellite and the wave position center, i.e. the target, during the satellite movement; The entire continuous perception process in a dynamic scene is the accumulation of the signal-to-noise ratio. The satellite's trajectory is divided into arcs of equal length. The length of each arc does not exceed 0.5 km. The distance between the satellite and the target in this arc uses the same value. To express, It is calculated from the time the satellite has moved before reaching the arc and the above time-distance relationship, thereby converting the satellite's dynamic accumulation process into the superposition of multiple static accumulation processes; By calculating the accumulated signal-to-noise ratio until the minimum signal-to-noise ratio required for perception is met, the dynamic accumulation time required to complete the perception task is obtained: ， in, For the The accumulated signal-to-noise ratio within the segment arc, For the The time of the satellite's motion within the arc, For the The satellite target distance within the segment arc and the satellite dynamic perception required time are expressed as: .

7. The method for efficiently allocating synaesthesia resources for a low-orbit communication satellite according to claim 1, characterized in that: In step 4, each ground wave position is divided into grids based on longitude and latitude, and the communication resource requirement of the ground wave position is determined by calculating the sum of the traffic volume of all grids. , including: Step 4.1: The weighting factor for the geographical location of land is , using the gross regional product per unit area To measure the economic development of a region, the economic weighting factor The calculation formula is as follows: ， ， in, The total area of ​​the grid value, is the size of the grid, is the maximum regional GDP per unit area in all grids; Step 4.2: The weighting factor for the geographical location of an ocean or lake is , using the ship traffic weighting factor To measure the traffic differences between grids: ， in, is the number of ships in the grid obtained by querying the ship positioning, is the maximum number of ships in all grids, and the traffic intensity factor of each grid It is expressed as: ； Step 4.3: Combine the basic communication rate of the area , the grid traffic intensity within the ground wave position is counted to obtain the communication traffic demand of the ground wave position : 。 8. The method for efficiently allocating synaesthesia resources for a low-orbit communication satellite according to claim 1, characterized in that: The step 5 specifically comprises the following steps: Step 5.1, choose to use the interawareness integrated time slot to realize the reuse of time slot resources within the beam hopping period to achieve basic interawareness function. In order to ensure basic communication capabilities, choose to use the second-order difference objective function as the optimization target: ， in, For the The communication traffic provided by each wave bit is For the The communication traffic required for each wave position is is the number of wave positions in the cluster; Step 5.2: After the optimization target is determined, the time slot joint optimization must meet the following constraints: a. Communication constraints: ， in, To meet the needs of both communication and perception, For the wave position that only needs communication, For the The number of time slots allocated to each wave position, is the total number of time slots in the beam hopping period, is the maximum number of beams working simultaneously in the cluster; The amount of communication traffic provided by the beam With the number of time slots The relationship is: ， in, is the communication loss coefficient, Total communication capacity provided for the synaesthesia integration system; b. Perception constraints: ， in, is the perceived performance loss coefficient, is the length of a single time slot, The shortest required perception time is equal to the perception demand time ; Step 5.3: Convert the second-order difference function optimization under constraints in step 5.1 into a convex optimization problem, and use the convex optimization toolbox to solve the integer solution for time slot allocation. .

9. The method for efficiently allocating synaesthesia resources for a low-orbit communication satellite according to claim 1, characterized in that: The step 6 specifically includes the following steps: Step 6.1, according to the time slot allocation solutions of each wave position obtained in step 5, arrange them in order of the number of time slots from small to large, so that the wave position with a small number of time slots is allocated first; Step 6.2: Consider all beam positions and ensure that the time slots of all beam positions are allocated within the maximum synchronization retention time of the communication user terminal, except for the already allocated beam positions. Move the time slots of the beam positions that have not appeared to the front to make the beam revisit time The maximum time to keep synchronization with the communication user terminal user Between, satisfy ; Step 6.3: Consider a single beam position. The intervals of all time slots of this beam position cannot exceed the maximum interruption time of target perception. The time slots exceeding the interruption time are moved to the front to make the beam revisit time Maximum interruption time with target perception ,satisfy ; Step 6.4: After the time slot number arrangement in step 6.1 and the time slot shifting in steps 6.2 and 6.3, a beam hopping pattern is obtained.

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