Satellite communication sea wave blockage modeling and quantification method for unmanned surface vehicle

Abstract

The present application relates to a kind of unmanned surface vehicle satellite communication sea wave shelter modeling and quantification method in the field of satellite communication.The present application constructs three-dimensional sea wave statistical distribution model in complex marine environment, compared with the traditional sea wave model based on wave energy spectrum, expand time and space dimension, it is more advantageous to describe the randomness of sea wave distribution.The present application innovatively introduces random geometry theory into sea wave shelter modeling, compared with the traditional wave height calculated by linear wave theory, no longer rely on historical experience to estimate the vertical distance between wave crest and wave trough.The present application calculates the probability of sea-air satellite communication link being sheltered by sea wave, and innovatively gives the quantification method of sea-air satellite communication link communication capacity and connectivity, does not depend on any signal system, can be adapted to different types of unmanned surface vehicle to the maximum extent.The modeling method of the present application can match the high sea condition application scene of unmanned surface vehicle, the quantification method can guide the parameter configuration of sea-air satellite communication link, and has engineering practice value.

Description

Technical Field

[0001] This invention relates to channel modeling technology in the field of satellite communication, especially in satellite internet where the marine environment is complex and air-to-ground links are frequently interacting. Using the method of this invention, an accurate wave obstruction model can be provided for unmanned surface vessels to use satellite communication, thereby improving the reliability and connectivity of satellite-to-ground communication links. Background Technology

[0002] With the rapid development of the blue economy, the demand for maritime communication is increasing daily. The global deployment of low-Earth orbit (LEO) satellite internet provides a broadband, high-capacity space-based communication network for shipping logistics, marine fisheries, maritime law enforcement, and resource exploration. It offers a new approach to solving the problems of weak signals, high latency, and high costs associated with traditional maritime communication relying on ground base stations and high-Earth orbit satellites in areas such as the open sea and polar regions. Among these technologies, unmanned surface vessels (USVs) are increasingly favored by the industry due to their maneuverability, ease of deployment, and low cost. They are not only becoming intelligent nodes in the maritime information network but also indispensable nerve endings for marine economic development, security maintenance, and scientific research.

[0003] However, due to limitations in platform size and payload, unmanned surface vessels (USVs) experience large yaw and pitch angles and low antenna elevation angles when navigating in complex marine environments, making them highly susceptible to physical obstruction from ocean waves. This leads to a sharp drop in the signal-to-noise ratio (SNR) of satellite communication, a surge in the bit error rate, and even signal loss. To maintain connectivity, terminals may increase transmission power or frequently attempt reconnection, further wasting the already power-constrained resources of the USV and shortening mission duration. Currently, satellite communication channel modeling focuses primarily on air-to-ground links, with limited research on sea-to-air links. Wave distribution models characterized by the Pearson-Moskowitz and JONSWAP wave spectra describe the distribution of wave energy at different frequencies by incorporating wind speed, but they cannot describe the locational attributes of wave distribution and cannot establish a direct mapping relationship with highly directional satellite channels. In particular, wave obstruction modeling for USV satellite communication remains lacking. Therefore, the targeted development of wave obstruction modeling and quantification methods for USVs is of paramount importance. Summary of the Invention

[0004] The purpose of this invention is to address the problem that unmanned surface vessel (USV) satellite communication links are highly susceptible to ocean surge blockage. This invention designs a method for modeling and quantifying ocean surge blockage in USV satellite communication, thereby optimizing USV satellite communication transmission parameters and improving the reliability of sea-air satellite communication links.

[0005] The technical solution adopted in this invention is as follows:

[0006] A method for modeling and quantifying wave obstruction in satellite communication for unmanned surface vessels includes the following steps:

[0007] S1. Based on the receiving gain of the low-orbit satellite antenna, the effective transmission power and transmission gain of the unmanned surface vessel antenna, the wave blockage loss function related to the position and time of the waves, and the free space loss function of the sea-air-satellite communication signal, a sea-air-satellite communication link loss model is constructed to represent the effective receiving power of the low-orbit satellite antenna.

[0008] S2 considers ocean waves as three-dimensional structures with centers of mass, around which several wave aftershocks are randomly scattered, forming a density of... The three-dimensional Poisson cluster process, i.e., 3D PCP, yields the three-dimensional wave probability distribution function P. sw Among them, density It is represented by the centroid density related to the wave position and the wave aftershock density related to time;

[0009] S3, divide all ocean waves into k layers, and the density of each layer of ocean waves is expressed as: Based on the three-dimensional ocean wave probability distribution function P sw The probability function obtained is that the signal emitted by the unmanned surface vessel toward the satellite is blocked by any u layer among all k layers of ocean waves. ;

[0010] S4. Differentiate the 3D PCP wave probability distribution function after layering to obtain the 2D PCP wave distribution density, and then use the probability function... Obtain the two-dimensional mapped wave probability distribution function ;

[0011] S5, the signal-to-noise ratio (SNR) received by satellites in the sea-air uplink is obtained from the sea-air satellite communication link loss model, and the constraint condition is set that the SNR is greater than or equal to a set threshold ε. min The probability function that the satellite can correctly receive and demodulate the data, related to the position and time of the ocean waves, is obtained. The probability of successful communication is then... The probability of ocean wave obstruction for sea-air satellite communication links is: ;

[0012] S6, according to the probability function The satellite communication link connectivity function and the sea-air satellite communication capacity function related to the position and time of the ocean waves are obtained.

[0013] S7. Based on the satellite communication link connectivity function and the sea-air satellite communication link communication capacity function, if the connectivity is greater than or equal to the set value, the sea-air satellite communication link will communicate normally; if the connectivity is less than the set value and the communication capacity is greater than or equal to the rate requirement, the sea-air satellite communication link will communicate normally; if the connectivity is less than the set value and the communication capacity is less than the rate requirement, the antenna elevation angle and effective transmission power of the unmanned surface vessel antenna need to be adjusted.

[0014] Furthermore, the loss model for the sea-air satellite communication link constructed in S1 is expressed as follows:

[0015] (1)

[0016] In the formula, P r P represents the effective received power of a low-Earth orbit satellite antenna. t G represents the effective transmit power of the unmanned surface vessel's antenna. r G represents the receiving gain of a low-Earth orbit satellite antenna. t L represents the transmit gain of the unmanned surface vessel antenna. sw (v,t) represents the wave shading loss function, where v represents location and t represents time. Let L represent the free-space loss function of the air-sea satellite communication signal, θ represent the low-Earth orbit satellite altitude, θ represent the antenna elevation angle of the unmanned surface vessel antenna, and α represent the fading factor. This indicates other losses, including atmospheric scintillation and cloud / fog absorption.

[0017] Furthermore, the specific process of S2 is as follows:

[0018] If we consider ocean waves as three-dimensional structures with centers of mass, then the set of centers of mass... Around the center of mass of each wave, several aftershocks are randomly scattered, forming a density of The three-dimensional Poisson cluster process, i.e., 3D PCP; where R represents Euclidean space and the density is expressed as:

[0019] (2)

[0020] In the formula, the integrand is λ(v,t)=λ p (v)λ s (t), λ p (v) represents the position-dependent centroid density, λ s (t) represents the time-dependent wave aftershock density, where the wave centroid and wave aftershock follow independent and identically distributed distributions; the generated three-dimensional wave probability distribution function is obtained, expressed as:

[0021] (3)

[0022] In the formula, n = 0, 1, 2... is used to represent the space R. 3 The number of wave centers of mass in the inland sea.

[0023] Furthermore, the specific process of S3 is as follows:

[0024] All ocean waves are divided into k layers, where k is a positive integer; based on the independence of each cluster in the 3D PCP distribution, the density of each layer of ocean waves is expressed as: Let the number of waves in each layer be n / k; then the probability that the signal emitted by the unmanned surface vessel towards the satellite is blocked by any u layer among all k layers of waves is expressed as:

[0025] (4)

[0026] in, , .

[0027] Furthermore, the specific process of S4 is as follows:

[0028] Differentiating the 3D PCP wave distribution density yields the spatial R. 3 To space R 2 Mapped 2D PCP wave distribution density , represented as:

[0029] (5)

[0030] The two-dimensional mapped wave probability distribution function is obtained, expressed as:

[0031] (6)

[0032] Furthermore, the specific process of S5 is as follows:

[0033] Define the signal-to-noise ratio (SNR) received by satellites in the sea-air uplink as greater than or equal to a set threshold ε. min The probability of successful communication is the probability that the satellite receiver can correctly receive and demodulate the signal. The probability of ocean wave obstruction for sea-air satellite communication links is then... ;in,

[0034] (7)

[0035] In the formula, Indicates noise power.

[0036] Furthermore, the specific process of S6 is as follows:

[0037] The connectivity T of the sea-air-satellite communication link is quantified according to the following formula, namely

[0038] (8)

[0039] The communication capacity of the sea-air satellite communication link is quantified according to the following formula. ,Right now

[0040] (9)

[0041] The advantages of this invention compared to the prior art are:

[0042] 1. This invention constructs a three-dimensional statistical distribution model of ocean waves in complex marine environments. Compared with traditional wave energy spectrum-based wave models, it expands the temporal and spatial dimensions and has a greater advantage in describing the randomness of wave distribution.

[0043] 2. This invention innovatively introduces stochastic geometry theory into wave occlusion modeling. Compared with the traditional method of calculating wave height using linear wave theory, it no longer relies on historical experience values ​​to estimate the vertical distance between wave crests and troughs. The three-dimensional Poisson cluster process used can significantly improve the modeling accuracy.

[0044] 3. This invention innovatively provides a quantitative method for the communication capacity and connectivity of sea-air-satellite communication links by calculating the probability of sea-air-satellite communication links being blocked by ocean waves. The proposed method does not depend on any signal system, can be adapted to different types of unmanned surface vessels to the greatest extent, and can be modeled through software with minimal hardware modifications. Attached Figure Description

[0045] Figure 1 This is a usage scenario diagram of the present invention.

[0046] Figure 2 This is a spatial analysis diagram of the distribution of unmanned surface vessels and ocean waves designed in this invention.

[0047] Figure 3 This is a diagram of the three-dimensional Poisson cluster process wave occlusion model designed in this invention.

[0048] Figure 4 This is a mapping diagram of the two-dimensional Poisson cluster process wave occlusion model designed in this invention.

[0049] Figure 5 This is a logic diagram for optimizing the launch parameters of the unmanned surface vessel designed in this invention. Detailed Implementation

[0050] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0051] First, refer to Figure 1 The application scenarios of the method of the present invention are given.

[0052] A wave-obstruction modeling and quantification method for satellite communication of unmanned surface vessels (USVs) is applicable to USV-to-ground communication links in satellite internet. Low-Earth orbit (LEO) satellites are equipped with payloads and can transmit synchronization signals on schedule. Neighboring satellites are connected via inter-satellite links. The USV is equipped with a phased array antenna, and different phased array beams sequentially interact with overhead LEO satellites, maintaining contact with only one LEO satellite at a time.

[0053] The specific steps of the method described in this invention are as follows:

[0054] S1, construct the sea-air-satellite communication link loss model, expressed as:

[0055] (1)

[0056] In the formula, P r P represents the effective received power of a low-Earth orbit satellite antenna. t G represents the effective transmit power of the unmanned surface vessel's antenna. r G represents the receiving gain of a low-Earth orbit satellite antenna. t L represents the transmit gain of the unmanned surface vessel antenna. sw (v,t) represents the wave shading loss function, where v represents location and t represents time. Let L represent the free-space loss function of the sea-air satellite communication signal, θ represent the low-Earth orbit satellite altitude, θ represent the antenna elevation angle, and α represent the fading factor. This indicates other losses, such as atmospheric scintillation and cloud / fog absorption.

[0057] S2, refer to Figure 2 A three-dimensional wave distribution function is constructed. Since surging waves are usually perpendicular to the sea surface, assuming that the waves are considered as three-dimensional structures with centroids, the set of each centroid is... Several small wave aftershocks are randomly scattered around each center of mass, thus forming a density of The three-dimensional Poisson clustered point process (3D PCP). Here, R represents Euclidean space, and the density is expressed as:

[0058] (2)

[0059] Here, the integrand λ(v,t)=λ p (v)λ s (t), λ p (v) represents the position-dependent centroid density; λ s (t) represents the time-dependent wave aftershock density. The wave centroid and wave aftershock follow independent and identically distributed (i.i.d.) distributions. Therefore, the generated three-dimensional wave probability distribution function is expressed as:

[0060] (3)

[0061] In the formula, n = 0, 1, 2... is used to represent the space R. 3 The number of wave centers of mass in the inland sea.

[0062] S3, Geometric analysis of the relationship between the unmanned surface vessel (USV) and the distribution of ocean waves. (Refer to...) Figure 3The waves are divided into k layers, where k is a positive integer. Due to the independence of each cluster in the 3D PCP distribution, the density of each wave layer is expressed as... Let the number of waves in each wave layer be denoted as n / k. Therefore, the probability that a signal emitted by an unmanned surface vessel towards a satellite is blocked by any u-layer among all k wave layers is expressed as:

[0063] (4)

[0064] in, , .

[0065] S4, construct a two-dimensional mapped wave distribution function. (Refer to...) Figure 4 ,Will Figure 3 The three-dimensional Poisson cluster process wave occlusion model is mapped to a two-dimensional Poisson clustered point process (2D PCP) wave occlusion model. The 2D PCP wave distribution density is obtained through this mapping, and the mapping method is defined as spatial R... 3 To space R 2 The mapped wave density is the derivative of the original 3D PCP wave distribution density function, specifically expressed as:

[0066] (5)

[0067] Therefore, the constructed two-dimensional mapped wave distribution function is expressed as:

[0068] (6)

[0069] S5, calculate the probability of sea wave obstruction in the sea-air satellite communication link. Define the signal-to-noise ratio (SNR) received by satellites in the sea-air uplink as greater than or equal to a certain threshold ε. min The probability that a satellite can correctly receive and demodulate the signal is the probability of successful communication. At this point, the probability of ocean wave obstruction of the sea-air satellite communication link is... .in,

[0070] (7)

[0071] In the formula, Indicates noise power.

[0072] S6 quantifies the connectivity and communication capacity of the sea-air-satellite communication link. The connectivity T of the sea-air-satellite communication link is quantified according to the following formula:

[0073] (8)

[0074] Furthermore, the communication capacity of the sea-air-satellite communication link is quantified according to the following formula. ,Right now

[0075] (9)

[0076] S7, see reference Figure 5 Optimize the launch parameters of the unmanned surface vessel. Calculate connectivity and communication capacity according to step S6. The optimization criteria are as follows:

[0077] (1) If the connectivity is greater than or equal to 0.5, then the sea-air-satellite communication link is in normal operation;

[0078] (2) If the connectivity is less than 0.5 but the communication capacity is greater than or equal to the rate requirement R (R is determined by the actual application requirements), then the sea-air-satellite communication link will communicate normally.

[0079] (3) If the connectivity is less than 0.5 and the communication capacity is less than the rate requirement R (R is determined by the actual application requirements), the low-orbit satellite will transmit a synchronization signal to the unmanned surface vessel via an inter-satellite link through a nearby satellite, requiring adjustment of the antenna elevation angle θ and the effective transmission power P of the unmanned surface vessel antenna. t To ensure uninterrupted communication.

[0080] After completing the above steps, the modeling and quantification of wave obstruction for satellite communication of unmanned surface vessels is complete.

[0081] In summary, the wave obstruction modeling and quantification method for unmanned surface vessels (USVs) satellite communication designed in this invention expands the temporal and spatial dimensions compared to traditional wave distribution models, enabling a precise description of the randomness of wave distribution in three-dimensional space. The proposed modeling method is suitable for high sea state application scenarios for USVs, and the proposed quantification method can guide the parameter configuration of sea-air satellite communication links, demonstrating significant engineering practical value.

Claims

1. A method for modeling and quantifying wave occlusion in satellite communication for unmanned surface vessels, characterized in that, Includes the following steps: S1. Based on the receiving gain of the low-orbit satellite antenna, the effective transmitting power and transmitting gain of the unmanned surface vessel antenna, the wave blocking loss function related to the position and time of the waves, and the free space loss function of the sea-air-satellite communication signal, a sea-air-satellite communication link loss model is constructed, representing the effective receiving power of the low-orbit satellite antenna. S2 considers ocean waves as three-dimensional structures with centers of mass, around which several wave aftershocks are randomly scattered, forming a density of... The three-dimensional Poisson cluster process, i.e., 3D PCP, yields the three-dimensional wave probability distribution function P. sw ; Among them, density It is represented by the centroid density related to the wave position and the wave aftershock density related to time; S3, divide all ocean waves into k layers, and the density of each layer of ocean waves is expressed as: Based on the three-dimensional ocean wave probability distribution function P sw The probability function obtained is that the signal emitted by the unmanned surface vessel toward the satellite is blocked by any u layer among all k layers of ocean waves. ; S4. Differentiate the 3D PCP wave probability distribution function after layering to obtain the 2D PCP wave distribution density, and then use the probability function... Obtain the two-dimensional mapped wave probability distribution function ; S5, the signal-to-noise ratio (SNR) received by satellites in the sea-air uplink is obtained from the sea-air satellite communication link loss model, and the constraint condition is set that the SNR is greater than or equal to a set threshold ε. min The probability function of satellites being able to correctly receive and demodulate waves, related to the position and time of the waves, is obtained. The probability of successful communication is then... The probability of ocean wave obstruction for sea-air satellite communication links is: ; S6, according to the probability function The satellite communication link connectivity function and the sea-air satellite communication capacity function related to the position and time of the ocean waves are obtained. S7. Based on the satellite communication link connectivity function and the sea-air satellite communication link communication capacity function, if the connectivity is greater than or equal to the set value, the sea-air satellite communication link will communicate normally; if the connectivity is less than the set value and the communication capacity is greater than or equal to the rate requirement, the sea-air satellite communication link will communicate normally; if the connectivity is less than the set value and the communication capacity is less than the rate requirement, the antenna elevation angle and effective transmission power of the unmanned surface vessel antenna need to be adjusted.

2. The method for modeling and quantifying wave obstruction in satellite communication for unmanned surface vessels according to claim 1, characterized in that, The loss model of the sea-air-satellite communication link constructed in S1 is expressed as follows: （1） In the formula, P r P represents the effective received power of a low-Earth orbit satellite antenna. t G represents the effective transmit power of the unmanned surface vessel's antenna. r G represents the receiving gain of a low-Earth orbit satellite antenna. t L represents the transmit gain of the unmanned surface vessel antenna. sw (v,t) represents the wave shading loss function, where v represents location and t represents time. Let L represent the free-space loss function of the air-sea satellite communication signal, θ represent the low-Earth orbit satellite altitude, θ represent the antenna elevation angle of the unmanned surface vessel antenna, and α represent the fading factor. This indicates other losses, including atmospheric scintillation and cloud / fog absorption.

3. The method for modeling and quantifying wave obstruction in satellite communication for unmanned surface vessels according to claim 2, characterized in that, The specific process of S2 is as follows: If we consider ocean waves as three-dimensional structures with centers of mass, then the set of centers of mass... Around the center of mass of each wave, several aftershocks are randomly scattered, forming a density of The three-dimensional Poisson cluster process, i.e., 3D PCP; where R represents Euclidean space and the density is expressed as: （2） In the formula, the integrand is λ(v,t)=λ p (v)λ s (t), λ p (v) represents the position-dependent centroid density, λ s (t) represents the time-dependent wave aftershock density, where the wave centroid and wave aftershock follow independent and identically distributed distributions; the generated three-dimensional wave probability distribution function is obtained, expressed as: （3） In the formula, n = 0, 1, 2... is used to represent the space R. 3 The number of wave centers of mass in the inland sea.

4. The method for modeling and quantifying wave obstruction in satellite communication for unmanned surface vessels according to claim 3, characterized in that, The specific process of S3 is as follows: All ocean waves are divided into k layers, where k is a positive integer; based on the independence of each cluster in the 3D PCP distribution, the density of each layer of ocean waves is expressed as: Let the number of waves in each layer be n / k; then the probability that the signal emitted by the unmanned surface vessel towards the satellite is blocked by any u layer among all k layers of waves is expressed as: （4） in, , .

5. The method for modeling and quantifying wave obstruction in satellite communication for unmanned surface vessels according to claim 4, characterized in that, The specific process of S4 is as follows: Differentiating the 3D PCP wave distribution density yields the spatial R. 3 To space R 2 Mapped 2D PCP wave distribution density , is represented as: （5） The two-dimensional mapped wave probability distribution function is obtained, expressed as: （6）。 6. The method for modeling and quantifying wave obstruction in satellite communication for unmanned surface vessels according to claim 5, characterized in that, The specific process of S5 is as follows: Define the signal-to-noise ratio (SNR) received by satellites in the sea-air uplink as greater than or equal to a set threshold ε. min The probability of successful communication is the probability that the satellite receiver can correctly receive and demodulate the signal. The probability of ocean wave obstruction for sea-air satellite communication links is then... ;in, （7） In the formula, Indicates noise power.

7. A method for modeling and quantifying wave obstruction in satellite communication for unmanned surface vessels according to claim 6, characterized in that, The specific process of S6 is as follows: The connectivity T of the sea-air-satellite communication link is quantified according to the following formula, namely （8） The communication capacity of the sea-air satellite communication link is quantified according to the following formula. ,Right now （9）。

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