CN102221448B

CN102221448B - Method and system for determining maritime SAR (search and rescue) region, and SAR simulator

Info

Publication number: CN102221448B
Application number: CN 201110132594
Authority: CN
Inventors: 金一丞; 肖方兵; 尹勇; 张显库; 任鸿翔; 张秀凤; 刘秀文; 任俊生; 谷伟; 张新宇; 孙霄峰; 张百安; 李志华; 马烈
Original assignee: Dalian Maritime University
Current assignee: Dalian Maritime University
Priority date: 2011-05-20
Filing date: 2011-05-20
Publication date: 2012-12-26
Anticipated expiration: 2031-05-20
Also published as: CN102221448A

Abstract

The invention discloses a method and system for determining a maritime SAR (search and rescue) region, and a SAR simulator, wherein the method comprises the following steps of receiving a distress signal sent by a SAR target; generating a plurality of stochastic particles equivalent to the SAR target; calculating the integrated initial probability distribution of the plurality of stochastic particles on an electronic chart under various distress situations; calculating and displaying the integrated drift probability distribution of the plurality of stochastic particles on the electronic chart after a prearranged time according to the integrated initial probability distribution and prearranged environment information; and subsequently appointing the optimum SAR region according to the integrated drift probability distribution. The method comprehensively considers the various distress situations of a distress target so that the maritime SAR region can be determined more precisely, the SAR risk can be reduced and the previous SAR time is saved for the SAR target.

Description

Method and system for determining maritime search and rescue area and search and rescue simulator

Technical Field

The invention belongs to the technical field of maritime search and rescue, and particularly relates to a method and a system for determining maritime search and rescue areas and a search and rescue simulator.

Background

After a marine accident occurs, whether a search and rescue target can be effectively and quickly found and rescued is significant for reducing life and property loss. Since the search and rescue target is easily influenced by wind, wave, current and other factors to drift continuously, especially marine accidents often occur under severe weather conditions, so that it is very difficult to determine the position of the search and rescue target, and therefore, how to accurately determine the search and rescue area containing the search and rescue target becomes one of important links in the search and rescue process.

The Method for determining the maritime Search and rescue area provided by the prior art is based on the Classic Search Planning Method (CSPM), which originates from the Search theory created during the second world war due to the need of anti-submarine warfare. Because the popularity of the computer is not high at the moment, the method mainly adopts paper pen calculation, is only suitable for search planning under simple search and rescue conditions, and does not consider various uncertain factors which may influence the search and rescue area, such as: the method has the advantages that errors exist in the search and rescue area determined by the method, the search and rescue area containing the search and rescue target cannot be accurately determined, the search and rescue risk is increased, the search and rescue target is very likely to be unable to be rescued in time due to the fact that the determined search and rescue area is inaccurate, and therefore search and rescue time is delayed.

Disclosure of Invention

The embodiment of the invention aims to provide a method for determining a maritime search and rescue area, and aims to solve the problems that the search and rescue area is determined by the method for determining the maritime search and rescue area provided by the prior art based on a classical search planning method, so that the determined search and rescue area has errors, and the search and rescue risk is increased.

The embodiment of the invention is realized in such a way that a method for determining a maritime search and rescue area comprises the following steps:

receiving a distress signal sent by a search and rescue target, and generating a plurality of random particles respectively equivalent to the search and rescue target;

calculating the comprehensive initial probability distribution of the plurality of random particles on the electronic chart under various distress scenes according to the distress signals;

and calculating and displaying comprehensive drifting probability distribution of the plurality of random particles on the electronic chart after preset time according to the comprehensive initial probability distribution and pre-stored environment information, and then appointing an optimal search and rescue domain according to the comprehensive drifting probability distribution.

Wherein the step of calculating the integrated initial probability distribution of the plurality of random particles on the electronic chart under the plurality of distress scenarios may include the steps of:

calculating initial probability distribution of the plurality of random particles on the electronic chart under the corresponding distress scene respectively;

and superposing the initial probability distributions of the corresponding random particles on the electronic chart in different distress scenes to obtain a comprehensive initial probability distribution of the random particles on the electronic chart.

Further, the step of calculating the initial probability distribution of the plurality of random particles on the electronic chart under the corresponding distress scenario may include the following steps:

presetting weights of the plurality of distress scenes;

multiplying the number of the plurality of random particles with the weight of the plurality of distress scenes respectively to obtain the number of the random particles of the corresponding distress scenes;

and calculating the initial probability distribution of the random particles corresponding to the distress scene on the electronic chart under the corresponding probability distribution according to the initial probability distribution corresponding to the distress scene.

The initial probability distribution of the distress scene can be the probability distribution of the last distress position of the known search and rescue target based on the reference datum, the probability distribution of the planned air route of the known search and rescue target based on the reference datum or the probability distribution of the operation area of the known search and rescue target based on the reference datum.

When the initial probability distribution of the distress scene is the probability distribution based on the reference datum point of the known search and rescue target final distress position, the abscissa of the search and rescue target final distress position in the electronic chart coordinate system is X₀Ordinate is Y₀(ii) a The step of calculating an initial probability distribution of random particles corresponding to the distress scenario on the electronic chart under the corresponding probability distribution may be:

calculating the mean value (0, 0) and the mean square error (sigma) of random particles corresponding to the distress scene₁And σ₂Under the condition of (1), probability distribution density of two-dimensional normal distribution in the electronic chart coordinate system

Wherein X is the abscissa of the search and rescue target in the electronic chart coordinate system, Y is the ordinate of the search and rescue target in the electronic chart coordinate system, X and Y are independent of each other, and sigma is₁＝σ₂；

Translating the obtained two-dimensional normal distribution along the abscissa by X₀And simultaneously translating the obtained two-dimensional normal distribution along the ordinate by Y₀Namely, the initial probability distribution of the random particles corresponding to the distress scene on the electronic chart is obtained.

Wherein the step of calculating the comprehensive drift probability distribution of the plurality of random particles on the electronic chart after a preset time according to the comprehensive initial probability distribution and the pre-stored environmental information may include the steps of:

calculating the drift velocity of a plurality of random particles corresponding to the distress scene on the electronic chart according to pre-stored environmental information and wind pressure coefficient information corresponding to the search and rescue target;

according to pre-stored environmental information, calculating drift displacement of a plurality of random particles corresponding to a distress scene on the electronic chart after a preset time;

obtaining the drift positions of the plurality of random particles in the corresponding distress scene after the preset time according to the comprehensive initial probability distribution and the calculated drift velocity and drift displacement, and further generating the probability distribution of the corresponding particles;

and superposing the drift probability distributions of the corresponding random particles on the electronic chart in different distress scenes to obtain the comprehensive drift probability distribution of the random particles on the electronic chart.

Further, before the step of calculating drift speeds of a plurality of random particles corresponding to a distress scene on the electronic chart according to the pre-stored environmental information and the wind pressure coefficient information corresponding to the search and rescue target, the method may further include the following steps: prestoring the flow velocity of sea water surface layer ocean current, the wind speed 10 meters high from the sea surface, and a downwind direction wind speed slope coefficient, a downwind direction offset coefficient, a crosswind direction wind speed slope coefficient and a crosswind direction offset coefficient which are respectively corresponding to a search and rescue target in a distress scene and are 10 meters high from the sea surface; the step of calculating the drift velocity of the plurality of random particles on the electronic chart corresponding to the distress scene according to the pre-stored environmental information and the wind pressure coefficient information corresponding to the search and rescue target may include the following steps:

calculating a downwind direction wind pressure vector according to the prestored wind speed 10 m high from the sea surface, and a downwind direction wind speed slope coefficient and a downwind direction offset coefficient which are respectively corresponding to the search and rescue target in the distress scene and are 10 m high from the sea surface, wherein the relationship among the wind speed 10 m high from the sea surface, the downwind direction wind speed slope coefficient and the downwind direction offset coefficient which are 10 m high from the sea surface and the downwind direction wind pressure vector is satisfied: l is_d＝a_dW₁₀+b_dWherein W is₁₀The wind speed a is 10 m high from the sea surface_dThe slope coefficient of the wind speed in the downwind direction is 10 m high from the sea surface, b_dIs the downwind direction offset coefficient, L_dIs the wind pressure vector in the downwind direction;

calculating a cross wind direction wind pressure vector according to the pre-stored wind speed 10 m high from the sea surface, and a cross wind direction wind speed slope coefficient and a cross wind direction offset coefficient which are respectively corresponding to a search and rescue target in a scene in danger, wherein the wind speed 10 m high from the sea surface, the cross wind direction wind speed slope coefficient and the cross wind direction offset coefficient satisfy the relationship: l is_c＝a_cW₁₀+b_cWherein a is_cIs the slope coefficient of the wind speed in the crosswind direction, b_cIs the cross-wind direction offset coefficient, L_cThe wind pressure vector in the crosswind direction is obtained;

synthesizing the calculated downwind direction wind pressure vector and crosswind direction wind pressure vector into a wind pressure vector; and synthesizing the synthesized wind pressure vector and the pre-stored flow velocity of the sea water surface layer ocean current to obtain the drift velocity of the plurality of random particles corresponding to the distress scene on the electronic chart.

Further, before the step of calculating drift displacement of the plurality of random particles on the electronic chart after the preset time and corresponding to the distress scenario according to the pre-stored environmental information, the method may further include the following steps: prestoring the average flow velocity of ocean current with the depth of 0.5 m from the sea surface, the variance of flow velocity disturbance, the average value of wind speed with the height of 10 m from the sea surface, the variance of wind speed disturbance, and a downwind direction wind speed slope coefficient, a downwind direction offset coefficient, a crosswind direction wind speed slope coefficient, a crosswind direction offset coefficient and a wind pressure coefficient disturbance variance which are respectively corresponding to search and rescue targets in a scene in danger and are 10 m from the sea surface; the step of calculating the drift displacement of the plurality of random particles on the electronic chart after the preset time and corresponding to the distress scene according to the pre-stored environmental information may include the steps of:

calculating according to the pre-stored average value of the wind speed 10 m high from the sea surface and the wind speed disturbance to obtain the wind speed 10 m high from the sea surface, wherein the average value of the wind speed 10 m high from the sea surface, the wind speed disturbance and the wind speed 10 m high from the sea surface satisfy the following relation:wherein,

the average value of the wind speed 10 meters high from the sea surface is shown, u 'is the wind speed disturbance, the mean value of the wind speed disturbance u' is 0, and the disturbance variance is sigma_WRandomly extracting in the circular normal distribution;

calculating a downwind direction wind speed slope coefficient estimation value which is corresponding to a search and rescue target in a distress scene and is 10 meters away from the sea surface according to the prestored downwind direction wind speed slope coefficient which is 10 meters away from the sea surface and the prestored wind pressure coefficient disturbance, wherein the downwind direction wind speed slope coefficient estimation value which is 10 meters away from the sea surface, the downwind direction wind speed slope coefficient disturbance and the downwind direction wind speed slope coefficient estimation value which is 10 meters away from the sea surface satisfy the relationship: a is_1d＝a_d+ τ/20, wherein, a_1dIs the estimation value of the slope coefficient of the wind speed in the downwind direction with the distance of 10 meters from the sea surface, wherein tau is the disturbance of the wind pressure coefficient, the mean value of the disturbance of the wind pressure coefficient tau is 0, and the disturbance variance is sigma_LCircle ofRandomly extracting in the shape normal distribution; calculating a downwind direction offset coefficient estimation value which is 10 m high from the sea surface and corresponds to a search and rescue target in a distress scene according to the downwind direction offset coefficient and the wind pressure coefficient disturbance which are prestored, wherein the downwind direction offset coefficient, the wind pressure coefficient disturbance and the downwind direction offset coefficient estimation value which is 10 m high from the sea surface satisfy the relationship: b_1d＝b_d+ τ/2, wherein b_1dThe estimated value of the downwind direction offset coefficient is 10 meters away from the sea surface; calculating to obtain a downwind direction wind pressure vector according to the downwind direction wind speed slope coefficient estimated value, the downwind direction offset coefficient estimated value and the wind speed 10 meters away from the sea surface;

calculating a cross wind direction wind speed slope coefficient estimation value which is 10 m away from the sea surface and corresponds to a search and rescue target in a scene in danger according to a pre-stored cross wind direction wind speed slope coefficient which is 10 m away from the sea surface and a wind pressure coefficient disturbance, wherein the cross wind direction wind speed slope coefficient which is 10 m away from the sea surface, the wind pressure coefficient disturbance and the cross wind direction wind speed slope coefficient estimation value which is 10 m away from the sea surface satisfy the relationship: a is_1c＝a_c+ τ/20, wherein, a_1cThe estimated value of the slope coefficient of the wind speed in the crosswind direction is 10 meters away from the sea surface; calculating a crosswind direction offset coefficient estimation value which is 10 m high from the sea surface and corresponds to a search and rescue target in a distress scene according to a prestored crosswind direction offset coefficient and a prestored wind pressure coefficient disturbance, wherein the crosswind direction offset coefficient, the wind pressure coefficient disturbance and the crosswind direction offset coefficient estimation value which is 10 m high from the sea surface satisfy the relationship: b_1c＝b_c+ τ/2, wherein b_1cThe cross wind direction offset coefficient estimation value is 10 m high from the sea surface; calculating to obtain a crosswind direction wind pressure vector according to the calculated crosswind direction wind speed slope coefficient estimated value, crosswind direction offset coefficient estimated value and the wind speed 10 meters away from the sea surface;

synthesizing the calculated downwind direction wind pressure vector and crosswind direction wind pressure vector into a wind pressure vector;

according to the pre-stored average flow velocity of the ocean current with the depth of 0.5 m from the sea surface, calculating the flow velocity disturbance to obtain the surface layer ocean current flow velocity of the sea water, wherein the average flow velocity of the ocean current with the depth of 0.5 m from the sea surface, the flow velocity disturbance and the surface layer ocean current flow velocity of the sea water meet the relationship:

wherein,

the average current velocity of the ocean current with the depth of 0.5 m from the sea surface, w 'is the current perturbation, the current perturbation w' is 0 from the mean value, and the perturbation variance is sigma_CRandomly extracting in the circular normal distribution;

according to the synthesized wind pressure vector and the calculated sea water surface layer ocean current flow velocity, calculating the drift displacement of a plurality of random particles on the electronic chart corresponding to a distress scene after a preset time, wherein the wind pressure vector, the sea water surface layer ocean current flow velocity and the drift displacement of the plurality of random particles on the electronic chart satisfy the following relations:wherein S (t) is the position of the random particles on the electronic chart after a preset time, S₀Initial positions of random particles on the electronic chart, S (t) -S₀The drift displacement of random particles on the electronic chart is shown, t is preset drift time, C (t) is the flow velocity of surface ocean current of the sea water, and L (t) is a wind pressure vector.

Another object of an embodiment of the present invention is to provide a system for determining a maritime search and rescue area, the system including:

the environment information storage unit is used for prestoring environment information and an electronic chart;

the signal receiving unit is used for receiving a distress signal sent by the search and rescue target;

a particle generation unit configured to generate a plurality of random particles equivalent to the search and rescue target, respectively;

a comprehensive initial probability distribution calculating unit, configured to calculate, according to the distress signal received by the signal receiving unit, a comprehensive initial probability distribution of the plurality of random particles generated by the particle generating unit on the electronic chart stored in the environment information storage unit;

a comprehensive drift probability distribution calculating unit, configured to calculate, according to the comprehensive initial probability distribution calculated by the comprehensive initial probability distribution calculating unit and the environment information pre-stored in the environment information storage unit, a comprehensive drift probability distribution of the plurality of random particles generated by the particle generating unit on the electronic chart after a preset time;

the display unit is used for displaying the comprehensive drift probability distribution calculated by the comprehensive drift probability distribution calculating unit;

and the search and rescue domain specifying unit is used for specifying an optimal search and rescue domain according to the comprehensive drift probability distribution calculated by the comprehensive drift probability distribution calculating unit.

Another objective of an embodiment of the present invention is to provide a search and rescue simulator, which includes a system for determining a maritime search and rescue area, where the system for determining a maritime search and rescue area includes:

The method for determining the maritime search and rescue area provided by the embodiment of the invention adopts a random particle simulation method, a search and rescue target is equivalent to a plurality of random particles, the comprehensive initial probability distribution of the random particles on an electronic chart under different distress scenes and the comprehensive drifting probability distribution of the random particles after the preset time are calculated, and then the comprehensive drifting probability distribution is visually displayed to designate an optimal search and rescue area.

Drawings

The present invention will be described in detail below with reference to the accompanying drawings and specific examples.

FIG. 1 is a flow chart of a method for determining a maritime search and rescue area according to an embodiment of the present invention;

FIG. 2 is an exploded view of a wind pressure according to an embodiment of the present invention;

FIG. 3 is a schematic block diagram of a system for determining a search and rescue area in the sea according to an embodiment of the present invention;

fig. 4 is a comprehensive drift probability distribution diagram of random particles at a time when T is 0min, T is 130min, and T is 230min, which is obtained by using the method for determining the maritime search and rescue area according to the embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

Fig. 1 shows a flow of a method for determining a maritime search and rescue area according to an embodiment of the present invention.

In step S101, a distress signal transmitted by a search and rescue target is received, and a plurality of random particles each equivalent to the search and rescue target are generated.

Each random particle has the same attribute as the search and rescue target and is subjected to the action of the external marine environment (such as wind, stream and the like) to drift, and the position of each random particle at any moment is irrelevant to the position of each random particle before the random particle in the drift process. For each random particle, the drift speed of the random particle is influenced by the marine environment factor and the wind pressure attribute factor of the search and rescue target, and different search and rescue targets (such as people falling into water, lifeboats and the like) have different wind pressure attributes of the search and rescue targets.

In step S102, a comprehensive initial probability distribution of a plurality of random particles on the electronic chart under a plurality of distress scenes is calculated according to the distress signal. The distress signal at least comprises position information of a search and rescue target and identification code information of communication equipment, and in addition, the distress signal also can comprise distress time, distress nature, necessary rescue form, navigation speed, course, ship name, type, national call number, contact way and other information.

Specifically, the step may include the steps of: calculating initial probability distribution of a plurality of random particles on an electronic chart under corresponding distress scenes respectively, wherein the distress scenes refer to a series of facts and assumptions describing possible situations of survivors, and generally consist of a series of or hypothetical events before a distress accident happens, and different distress scenes have different initial probability distribution due to different wind pressure attributes of search and rescue targets and/or information obtained from distress signals; and overlapping the initial probability distributions of the corresponding random particles on the electronic chart in different distress scenes to obtain the comprehensive initial probability distribution of the plurality of random particles on the electronic chart.

In view of the fact that the search and rescue information obtained from the distress signal or other approaches has different credibility, the search and rescue target generally includes multiple distress scenes and different distress scenes have different weights, and in order to obtain the initial probability distribution of the random particles more accurately, in the embodiment of the present invention, the step of calculating the initial probability distribution of the multiple random particles on the electronic chart under the corresponding distress scenes may further include the following steps: presetting weights of a plurality of distress scenes; multiplying the number of the plurality of random particles with the weight of the plurality of distress scenes respectively to obtain the number of the random particles of the corresponding distress scenes; and calculating the initial probability distribution of the random particles corresponding to the distress scene on the electronic chart under the corresponding probability distribution according to the initial probability distribution corresponding to the distress scene. For example, assume that the number of random particles equivalent to the search and rescue target is J, there are N (N ≧ 1) distress scenes, and the weight of the nth (1 ≦ N ≦ N) distress scene is q_nThen there is

The number of random particles in the nth distress scenario is q_nX J, q of_nThe xJ random particles obey the initial probability distribution corresponding to the nth distress scene, and correspondingly, the q random particles are calculated_nAnd (4) acquiring the initial probability distribution of the XJ random particles on the electronic chart under the initial probability distribution corresponding to the nth distress scene.

Preferably, the initial probability distribution of the distress scene can be a reference datum-based probability distribution of the last distress position of a known search and rescue target, a reference datum-based probability distribution of a planned route of a known search and rescue target, or a reference datum-based probability distribution of a known search and rescue target operation area (such as a fishing operation area, etc.). Under the probability distribution based on the reference datum points, the distribution of the random particles corresponding to the distress scene on the electronic chart is that the mean square error is sigma₁And σ₂The two-dimensional normal distribution of (1) is to set the coordinates of the position of the search and rescue target in the electronic chart coordinate system by adopting the abscissa X to represent the coordinates in the east-west direction and the ordinate Y to represent the coordinates in the north-south direction, and the coordinates of the position information of the search and rescue target sent by the search and rescue target after conversion in the electronic chart coordinate system are (X is the X coordinate)₀，Y₀) Then, the step of calculating the initial probability distribution of the random particles corresponding to the distress scene on the electronic chart under the corresponding probability distribution specifically includes: calculating the mean value (0, 0) and the mean square error (sigma) of random particles corresponding to the distress scene₁And σ₂Under the condition of (1), probability distribution density of two-dimensional normal distribution in the electronic chart coordinate system

May take sigma₁＝σ₂X and Y are independent from each other, so that the two-dimensional normal distribution is a circular normal distribution; translating the obtained circular normal distribution along the abscissa by X₀Simultaneously translating the obtained circular normal distribution along the ordinate by Y₀Namely, the initial probability distribution of the random particles on the electronic chart corresponding to the distress scene. Under the probability distribution based on the reference datum line, the distribution of random particles corresponding to the distress scene on the electronic chart is normal distribution which is transversely symmetrical along the search and rescue target planned route, the closer the transverse distance to the search and rescue target planned route is, the higher the probability of distress at the position is, and the farther the transverse distance to the search and rescue target planned route is, the lower the probability of distress is. Under probability distribution based on reference datum region, random particles corresponding to distress scene are in electronThe distribution on the chart is a uniform distribution within an operating area.

In step S103, a comprehensive drift probability distribution of the plurality of random particles on the electronic chart after a preset time is calculated and displayed according to the comprehensive initial probability distribution, the pre-stored environmental information, and the wind pressure coefficient information corresponding to the search and rescue target, and then an optimal search and rescue domain is designated according to the comprehensive drift probability distribution.

Specifically, the step of calculating the comprehensive drift probability distribution of the plurality of random particles on the electronic chart after the preset time according to the comprehensive initial probability distribution, the pre-stored environmental information and the wind pressure coefficient information corresponding to the search and rescue target comprises the following steps: calculating the drift velocity of a plurality of random particles corresponding to the distress scene on the electronic chart according to the pre-stored environmental information and the wind pressure coefficient information corresponding to the search and rescue target; according to pre-stored environmental information, calculating drift displacement of a plurality of random particles on the electronic chart, corresponding to the distress scene, after a preset time; obtaining the drift positions of a plurality of random particles in the corresponding distress scene after preset time by integrating the initial probability distribution and the drift direction and the drift displacement obtained by calculation, and further generating the probability distribution of the corresponding particles; and overlapping the drift probability distribution of the corresponding random particles on the electronic chart in different distress scenes to obtain the comprehensive drift probability distribution of the plurality of random particles on the electronic chart.

The drift velocity of the random particles on the electronic chart is determined by the wind pressure vector and the flow velocity C of the surface ocean current of the sea water. The wind pressure refers to the part of the search and rescue target above the water due to the action of wind, so that the search and rescue target generates relative motion to the surrounding water, and the relative motion is a vector and is represented by two quantities, namely the magnitude of the wind pressure and the direction of the wind pressure. The magnitude of the wind pressure refers to the movement speed of the search and rescue target relative to the surrounding water, and the direction of the wind pressure refers to the angle of the search and rescue target deviating from the downwind direction, and the angle is called a wind pressure angle. The shape, size and movement direction of the search and rescue target and the area ratio of the upper part and the lower part of the search and rescue target have influence on the wind pressure, and the wind pressure and the wind are generally determined according to an empirical method in practiceThe correspondence between the speeds. FIG. 2 is a schematic exploded view of wind pressure, where L is a wind pressure vector, α is a wind pressure angle, and L is a wind pressure_dA downwind direction wind pressure vector L of which the wind pressure is decomposed along the downwind direction_cThe cross wind direction wind pressure vector is decomposed along the vertical downwind direction by the wind pressure, and the relationship between the cross wind direction wind pressure vector and the vertical downwind direction wind pressure vector satisfies the following conditions: l is_d＝|L|cosα；L_c＝|L|sinα。

Downwind direction wind pressure vector L_dThe relation between the wind speed and the wind speed 10 m high from the sea surface satisfies the formula 1: l is_d＝a_dW₁₀+b_dWherein W is₁₀Wind speed 10 m high from sea surface, a_dAnd b_dIs a regression coefficient of wind pressure, a_dIs the downwind direction wind speed slope coefficient of 10 m high from the sea surface, b_dFor the downwind direction offset coefficient, similarly, the wind speed slope coefficient a in the known crosswind direction_cAnd cross wind direction offset coefficient b_cUnder the condition of (2), the wind pressure vector L in the crosswind direction can be obtained_c. Different search and rescue targets have different wind pressure attributes, a_d、b_d、a_cAnd b_cThe values of the wind pressure values are different, for the same search and rescue target, the probability of the same search and rescue target about the wind direction under the deviation in the initial state is equal, the deviation direction of the drift cannot be accurately determined before the drift motion, but once the same search and rescue target drifts along a certain direction, the wind pressure direction cannot be changed.

Therefore, before the step of calculating the drift velocity of a plurality of random particles corresponding to the distress scene on the electronic chart according to the pre-stored environmental information and the wind pressure coefficient information corresponding to the search and rescue target, the method further comprises the following steps: prestoring the surface sea current flow rate C of the sea water as environmental information and the wind speed W10 m high from the sea surface₁₀And the downwind direction wind speed slope coefficient a which is 10 meters high away from the sea surface and corresponds to the search and rescue target respectively_dDownwind direction offset coefficient b_dThe slope coefficient a of the wind speed in the crosswind direction_cCross wind direction offset coefficient b_c(ii) a At the moment, a plurality of follow-up wind pressure coefficients corresponding to the distress scene are calculated according to prestored environment information and wind pressure coefficient information corresponding to the search and rescue targetThe drift velocity of the organic particles on the electronic chart specifically comprises the following steps: according to the prestored wind speed W which is 10 m high from the sea surface₁₀And the downwind direction wind speed slope coefficient a which is 10 meters away from the sea surface and corresponds to the search and rescue target in the scene of distress respectively_dDownwind direction offset coefficient b_dCalculating the wind pressure vector L in the downwind direction_d(ii) a According to the prestored wind speed W which is 10 m high from the sea surface₁₀And the slope coefficient a of the cross wind direction wind speed corresponding to the search and rescue target in the scene of distress respectively_cCross wind direction offset coefficient b_cCalculating the wind pressure vector L in the crosswind direction_c(ii) a The calculated downwind direction wind pressure vector L_dWind pressure vector L in crosswind direction_cSynthesizing a wind pressure vector L; and synthesizing the synthesized wind pressure vector L and the prestored sea surface current flow velocity C of the sea water to obtain the drift velocity of a plurality of random particles on the electronic chart corresponding to the distress scene. It should be understood by those skilled in the art that in order to make the determined search and rescue area more accurate, a plurality of random particles can obtain two symmetric drift velocity directions under the corresponding distress scene by deviating from the downwind direction.

For the drift displacement of random particles on the electronic chart, after the search and rescue target is in danger, the random particles drift under the combined action of three forces of wind, wave and flow on the sea, and according to Newton's second law, the acceleration equation is as follows:wherein V is the drift speed of the search and rescue target, Sigma F is the sum of external forces applied to the search and rescue target, and F_aAs drag force of wind, F_wRadiation force of waves, F_cThe additional mass m' is derived from the acceleration of water particles attached to the surface of the search and rescue target as the dragging force of the flow; while

F_w＝1/2C_iwgρ_wL_tA²，Wherein, C_dAnd C_cdRespectively drag coefficient of wind and drag coefficient of flow, C_iwIs the reflection coefficient of the wave, p_aAnd ρ_wRespectively the density of air and the density of sea water, A_aAnd A_wThe areas of the water part and the underwater part of the search and rescue target are respectively, A is the wave amplitude of waves, W_aAnd L_bRespectively sea surface wind speed and wind-induced drift speed, L, of search and rescue target_tG is the gravity acceleration, which is the length of the search and rescue target. It will be appreciated by those skilled in the art that the radiation force F of the wave is small when the length of the search and rescue target is small relative to the wavelength of the wave (typically less than 50 meters), for example when the search and rescue target is ship debris, man in water, lifeboat raft, small aircraft, etc_wCan be ignored, therefore, the drift velocity V of the search and rescue target is V_curr+V_relWherein V is_currThe speed of ocean current to the ground is composed of surface ocean current and wave-induced Stokes drift, and the surface ocean current comprises Eckman drift, inclined pressure movement, tidal current, inertia current and the like; v_relFor the speed of the search and rescue target on the surrounding seawater, the influence of wind and sea waves on the drift speed of the search and rescue target is reflected, the influence of wind pressure is mainly exerted, namely the influence of waves on the drift of the search and rescue target is not considered, and the drift speed V of the search and rescue target can be expressed as follows: v is C + L, where C is the flow velocity of the surface ocean current of the seawater and L is the wind-induced drift velocity (wind pressure); at this time, the drift displacement S (t) -S of the search and rescue target₀Satisfies formula 2:

wherein S (t) is the position of the search and rescue target on the electronic chart after the preset time, S₀The initial position of the search and rescue target on the electronic chart, S (t) -S₀The drift displacement of the search and rescue target on the electronic chart is shown, t is preset drift time, C (t) is the flow velocity of surface ocean current of the sea water, and L (t) is a wind pressure vector.

In the examples of the present invention, W₁₀The wind pressure vector L can be calculated by taking the average wind speed 10 m high from the sea surface, and the surface layer current velocity C can be taken from the sea 0.5 m deep from the sea surfaceFlow average flow velocity, and calculating the drift velocity of the random particles according to the wind pressure vector L and the surface ocean current flow velocity C, thereby obtaining the drift displacement S (t) -S of the search and rescue target₀。

Therefore, before the step of calculating the drift displacement of the plurality of random particles on the electronic chart corresponding to the distress scene after the preset time according to the pre-stored environmental information, the method may further include the following steps: prestoring the surface sea current flow rate C of the sea water as environmental information and the wind speed W10 m high from the sea surface₁₀And the downwind direction wind speed slope coefficient a which is 10 meters away from the sea surface and corresponds to the search and rescue target in the scene of distress respectively_dDownwind direction offset coefficient b_dThe slope coefficient a of the wind speed in the crosswind direction_cCross wind direction offset coefficient b_c(ii) a At this time, according to the pre-stored environmental information, the step of calculating the drift displacement of the plurality of random particles on the electronic chart corresponding to the distress scene after the time is set specifically is as follows: according to the prestored wind speed W which is 10 m high from the sea surface₁₀And the downwind direction wind speed slope coefficient a which is 10 meters away from the sea surface and corresponds to the search and rescue target in the scene of distress respectively_dDownwind direction offset coefficient b_dCalculating the wind pressure vector L in the downwind direction_d(ii) a According to the prestored wind speed W which is 10 m high from the sea surface₁₀And the slope coefficient a of the cross wind direction wind speed corresponding to the search and rescue target in the scene of distress respectively_cCross wind direction offset coefficient b_cCalculating the wind pressure vector L in the crosswind direction_c(ii) a The calculated downwind direction wind pressure vector L_dWind pressure vector L in crosswind direction_cSynthesizing to obtain a wind pressure vector L; and calculating the drift displacement of a plurality of random particles on the electronic chart according to the synthesized wind pressure vector L and the prestored sea surface current flow velocity C of the sea water.

Further, in order to improve the accuracy of the determined search and rescue area, in the embodiment of the present invention, when calculating the drift displacement of the plurality of random particles on the electronic chart corresponding to the scene in distress, the environmental disturbance to which the random particles are subjected may be considered, and at this time, the flow velocity C of the surface ocean current of the seawater satisfies the formula three:

therein

Is the average current velocity at a depth of 0.5 m from the sea surface, and w 'is the current perturbation w' which is 0 from the mean and σ as the mean square error_CRandomly extracting in the circular normal distribution; downwind direction wind pressure vector L_dThe formula four is satisfied: l is_d＝a_1dW₁₀+b_1dWherein a is_1dThe estimation value of the slope coefficient of the wind speed in the downwind direction which is 10 meters away from the sea surface and corresponds to the search and rescue target in the scene in danger meets the formula V: a is_1d＝a_d+ τ/20, wherein b_1dThe estimation value of the downwind direction offset coefficient corresponding to the search and rescue target in the scene of distress and 10 meters away from the sea surface meets the formula six: b_1d＝b_d+ tau/2, tau in formula five and formula six is the disturbance of the wind pressure coefficient of the random particle, the disturbance of the wind pressure coefficient tau is 0 from the mean value, and the variance is sigma_LIs randomly extracted from the circular normal distribution of (1), wherein the wind speed W is 10 m high from the sea surface₁₀The formula seven is satisfied:

thereinIs the average value of wind speed 10 m high from sea surface, wherein u 'is wind speed disturbance, the wind speed disturbance u' is 0 from the average value, and the variance is sigma_WThe circular normal distribution of the wind pressure vector L can be randomly extracted and the wind pressure vector L in the crosswind direction can be obtained in the same way_cAnd according to the obtained downwind direction wind pressure vector L_dWind pressure vector L in crosswind direction_cAnd synthesizing to obtain the wind pressure vector L.

At this time, before the step of calculating the drift displacement of the plurality of random particles on the electronic chart corresponding to the distress scene after the preset time according to the pre-stored environmental information, the method may further include the following steps: prestoring distance sea surface as environment informationAverage flow velocity of ocean currents of 0.5 m depth

Variance σ of flow velocity disturbance w_CWind speed W10 m high from sea surface₁₀Average value of (2)

Variance σ of wind speed disturbance u_WAnd the downwind direction wind speed slope coefficient a which is 10 meters away from the sea surface and corresponds to the search and rescue target in the scene of distress respectively_dDownwind direction offset coefficient b_dThe slope coefficient a of the wind speed in the crosswind direction_cCross wind direction offset coefficient b_cVariance sigma of wind pressure coefficient disturbance tau_L(ii) a At this time, according to the pre-stored environmental information, the step of calculating the drift displacement of the plurality of random particles on the electronic chart, which corresponds to the distress scene after the preset time, is specifically as follows: calculating to obtain the wind speed W10 m high away from the sea surface according to the prestored average value of the wind speed 10 m high away from the sea surface and the wind speed disturbance u₁₀(ii) a According to the pre-stored downwind direction wind speed slope coefficient a which is 10 m high from the sea surface_dCalculating a downwind direction wind speed slope coefficient estimated value a which is 10 meters away from the sea surface and corresponds to a distress scene according to the wind pressure coefficient disturbance tau_1dAccording to the pre-stored downwind direction offset coefficient b_dCalculating a downwind direction offset coefficient estimation value b which is 10 meters away from the sea surface and corresponds to the scene of distress according to the wind pressure coefficient disturbance tau_1d(ii) a According to the calculated downwind direction wind speed slope coefficient estimated value a_1dDownwind direction offset coefficient estimation value b_1dAnd a wind speed W10 m high from the sea surface₁₀Calculating to obtain a wind pressure vector L in the downwind direction_d(ii) a According to a pre-stored crosswind direction wind speed slope coefficient a which is 10 m high from the sea surface_cCalculating a cross wind direction wind speed slope coefficient estimation value a corresponding to a search and rescue target in a distress scene and 10 meters away from the sea surface according to the wind pressure coefficient disturbance tau_1cAccording to the pre-stored cross wind direction offset coefficient b_cCalculating a cross wind direction offset coefficient estimation value b which is 10 meters away from the sea surface and corresponds to a distress scene according to the wind pressure coefficient disturbance tau_1c(ii) a According to the calculated wind speed slope coefficient estimated value a in the crosswind direction_1cCrosswind direction offset coefficient estimation value b_1cAnd a wind speed W10 m high from the sea surface₁₀Calculating to obtain a wind pressure vector L in the crosswind direction_c(ii) a The calculated downwind direction wind pressure vector L_dWind pressure vector L in crosswind direction_cSynthesizing to obtain a wind pressure vector L; according to the pre-stored average current velocity of the ocean current with the depth of 0.5 m from the sea surfaceCalculating the flow velocity disturbance w' to obtain the sea water surface ocean current flow velocity C; and calculating the drift velocity of the plurality of random particles on the electronic chart according to the synthesized wind pressure vector L and the calculated sea water surface layer sea current flow velocity C, and further calculating the drift displacement of the plurality of random particles on the electronic chart corresponding to the distress scene after preset time.

In order to facilitate intuitive display of the probability distribution of the random particles on the electronic chart, before step S102, the embodiment of the present invention may further include the following steps: dividing the electronic chart into two or more grid units, and in step S103, the step of specifying the optimal search and rescue area according to the comprehensive drift probability distribution is specifically: and determining the grid unit containing the maximum number of random particles as the optimal search and rescue domain according to the comprehensive drift probability distribution.

Fig. 3 shows a schematic structure of a system for determining an offshore search and rescue area according to an embodiment of the present invention.

The system for determining the search and rescue area on the sea comprises the following components: the environment information storage unit 8 is used for prestoring environment information and an electronic chart; the signal receiving unit 1 is used for receiving distress signals sent by search and rescue targets; a particle generation unit 2 for generating a plurality of random particles equivalent to search and rescue targets, respectively; a comprehensive initial probability distribution calculating unit 3, configured to calculate a comprehensive initial probability distribution of the plurality of random particles generated by the particle generating unit 2 on the electronic chart according to the distress signal received by the signal receiving unit 1; the comprehensive drift probability distribution calculating unit 4 is used for calculating comprehensive drift probability distribution of a plurality of random particles generated by the particle generating unit 2 on the electronic chart after preset time according to the comprehensive initial probability distribution calculated by the comprehensive initial probability distribution calculating unit 3 and the environmental information prestored by the environmental information storing unit 8; a display unit 5, configured to display the comprehensive drift probability distribution calculated by the comprehensive drift probability distribution calculating unit 4; and the search and rescue domain specifying unit 6 is used for specifying an optimal search and rescue domain according to the comprehensive drift probability distribution calculated by the comprehensive drift probability distribution calculating unit 4.

The distress signal at least comprises position information of a search and rescue target and identification code information of communication equipment, and in addition, the distress signal also can comprise distress time, distress nature, necessary rescue form, navigation speed, course, ship name, type, national call number, contact way and other information.

Specifically, the integrated initial probability distribution calculating unit 3 may include: a first calculating unit 31, configured to calculate initial probability distributions of the plurality of random particles generated by the particle generating unit 2 on the electronic chart in corresponding distress scenarios, respectively, where the distress scenarios refer to a series of facts and assumptions describing situations that survivors may occur, and generally consist of a series of events or hypothetical events from before a distress accident occurs to the present, and different distress scenarios have different probability distributions due to different wind pressure attributes of the search and rescue target and/or different information obtained from distress signals; the first superimposing unit 32 is configured to superimpose the initial probability distributions, on the electronic chart, of the corresponding random particles in different distress scenarios, which are obtained by the first calculating unit 31, so as to obtain a comprehensive initial probability distribution of the multiple random particles on the electronic chart.

More specifically, in consideration of the fact that the search and rescue information obtained from the distress signal or other approaches has different credibility and different distress scenes of the search and rescue target have different weights, in order to obtain the initial probability distribution of the random particles more accurately, the system for determining the maritime search and rescue area provided by the embodiment of the present invention may further include: the preset unit 7 is used for presetting the weights of a plurality of distress scenes and storing the preset weights of the plurality of distress scenes in the environment information storage unit 8; the first calculation unit 31 may further include: the first calculating module 311 is configured to multiply the number of the plurality of random particles generated by the particle generating unit 2 by the weights of the plurality of distress scenes stored in the environment information storage unit 8, respectively, to obtain the number of the random particles of the corresponding distress scene; the second calculating module 312 is configured to calculate, according to the initial probability distribution corresponding to the distress scenario, an initial probability distribution of the random particles corresponding to the distress scenario on the electronic chart under the corresponding probability distribution.

Preferably, the initial probability distribution of the distress scene may be a probability distribution based on a reference point of a last distress location of a known search and rescue target, a probability distribution based on a reference line of a planned route of a known search and rescue target, or a probability distribution based on a reference area of a known search and rescue target operation area (e.g., a fishing operation area, etc.), and the specific probability distribution is as described above and is not described herein again.

Specifically, the comprehensive drift probability distribution calculating unit 4 further includes: the drift velocity determining module 41 is configured to calculate drift velocities of a plurality of random particles on the electronic chart, which correspond to the distress scene, according to the environmental information pre-stored in the environmental information storage unit 8 and the wind pressure coefficient information corresponding to the search and rescue target; the drift displacement determining module 42 is configured to calculate drift displacements of a plurality of random particles on the electronic chart, which correspond to the distress scene after a preset time, according to the environment information pre-stored in the environment information storage unit 8; an obtaining module 43, configured to obtain, by the comprehensive initial probability distribution calculated by the comprehensive initial probability distribution calculating unit 3, the drift velocity calculated by the drift velocity determining module 41, and the drift displacement calculated by the drift displacement determining module 42, drift positions of the plurality of random particles in the corresponding distress scene after a preset time, and further generate probability distribution of the corresponding particles; the second superimposing unit 44 is configured to superimpose the drift probability distributions of the corresponding random particles on the electronic chart in different distress scenarios obtained by the obtaining module 43, so as to obtain a comprehensive drift probability distribution of the plurality of random particles on the electronic chart.

The step of calculating the drift velocity of the plurality of random particles on the electronic chart corresponding to the distress scene by the drift velocity determination module 41 is as described above, and the step of calculating the drift displacement of the plurality of random particles on the electronic chart corresponding to the distress scene by the drift displacement determination module 42 is as described above, and is not repeated herein.

In order to facilitate intuitive display of probability distribution of random particles on the electronic chart, the system for determining an offshore search and rescue area provided by the embodiment of the present invention may further include: the grid dividing unit 9 is configured to divide the electronic chart stored in the environment information storage unit 8 into two or more grid units, and the step of the search and rescue area specifying unit 6 specifying the optimal search and rescue area according to the comprehensive drift probability distribution calculated by the comprehensive drift probability distribution calculating unit 4 is specifically: the search and rescue domain specifying unit 6 determines the grid unit which contains the largest number of random particles and is divided by the grid dividing unit 9 as the optimal search and rescue domain according to the comprehensive drift probability distribution calculated by the comprehensive drift probability distribution calculating unit 4.

The embodiment of the invention also provides a search and rescue simulator comprising the system for determining the maritime search and rescue area.

To illustrate the effectiveness of the method for determining a maritime search and rescue area provided by the embodiment of the present invention, the method for determining a maritime search and rescue area is verified by using experimental data of 2nm (nautical miles) × 2nm (nautical miles) collected by staff at the university of atlantic ocean, florida, 3, 7 days, 1993 in the 2nm (nautical miles) region centered along the northmost end of the long-base viaduct in the atlantic ocean. Part of the experimental data is shown in the following table one:

the direction is a clockwise angle of the search and rescue target offset due to the north, the clockwise angle comprises actual observation position data of the people falling into water and environment information data of a wind field and a flow field corresponding to the actual observation position data, the mean square error of the wind field data is 0.78m/s, the mean square error of the flow field data is 0.17m/s, and the wind pressure coefficient data of the people falling into water is shown in the following table two:

according to the experimental data shown in the table I and the table II, the method for determining the maritime search and rescue area based on the classical search planning method provided by the prior art and the method for determining the maritime search and rescue area provided by the embodiment of the invention are respectively adopted, predicting the search and rescue area of the person falling into the water, taking the number J of random particles as 1000, instantly releasing the random particles in an error circle range which takes the initial release points (1392, -1064) of the person falling into the water on the electronic chart as the center of a circle and takes 380 meters as the radius, fig. 4 shows a comprehensive drift probability distribution of random particles at the time when T is 0min, T is 130min, and T is 230min, which is obtained by the method for determining a maritime search and rescue area provided by the embodiment of the present invention, the area A is a search and rescue area determined by a method for determining a maritime search and rescue area based on a classical search planning method, and the area B is the size of the search and rescue area determined by the method for determining the maritime search and rescue area provided by the embodiment of the invention. Due to the existence of wind field data errors, flow field data errors and wind pressure coefficient errors, the predicted search and rescue area continuously expands along with the time. The prediction result that the time T is 230min shows that the size of the search and rescue area determined by the method for determining the maritime search and rescue area provided by the embodiment of the invention is 60% of the size of the search and rescue area determined by the method for determining the maritime search and rescue area based on the classical search planning method, the accuracy of the search and rescue area is higher, and the time for subsequent search and rescue is saved.

The method for determining the maritime search and rescue area provided by the embodiment of the invention adopts a random particle simulation method, a search and rescue target is equivalent to a plurality of random particles, the comprehensive initial probability distribution of the random particles on an electronic chart under different distress scenes and the comprehensive drifting probability distribution of the random particles after preset time are calculated, and then the comprehensive drifting probability distribution is visually displayed to designate an optimal search and rescue area; in addition, when the drift distance of the random particles on the electronic chart is calculated, the environmental disturbances such as wind pressure disturbance and ocean current disturbance, and the like, which are suffered by the random particles, can be considered, and the determination accuracy of the search and rescue area is further improved.

The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.

Claims

1. A method of determining a maritime search and rescue area, the method comprising the steps of:

2. The method for determining a maritime search and rescue zone according to claim 1, wherein the step of calculating the integrated initial probability distribution of the plurality of random particles on the electronic chart under the plurality of distress scenarios comprises the steps of:

3. The method for determining a maritime search and rescue zone according to claim 2, wherein the step of calculating the initial probability distribution of the plurality of random particles on the electronic chart under the corresponding distress scene respectively comprises the following steps:

presetting weights of the plurality of distress scenes;

4. The method for determining maritime search and rescue zone according to claim 3, wherein the initial probability distribution of the distress scene is a reference-point-based probability distribution of a last distress location of a known search and rescue target, a reference-line-based probability distribution of a known search and rescue target planning route, or a reference-base-zone-based probability distribution of a known search and rescue target working zone.

5. The method for determining maritime search and rescue zone according to claim 4, wherein the initial probability distribution of the distress scene is a reference-point-based probability distribution of known search and rescue target last-distress locations, and the abscissa of the search and rescue target last-distress location in the electronic chart coordinate system is X₀Ordinate is Y₀(ii) a The step of calculating the initial probability distribution of the random particles corresponding to the distress scene on the electronic chart under the corresponding probability distribution is as follows:

Wherein X is the abscissa of the search and rescue target in the electronic chart coordinate system, Y is the ordinate of the search and rescue target in the electronic chart coordinate system, X and Y are independent of each other, and sigma is₁=σ₂；

6. The method for determining a maritime search and rescue area according to claim 1, wherein the step of calculating a comprehensive drift probability distribution of the plurality of random particles on the electronic chart after a preset time according to the comprehensive initial probability distribution and pre-stored environmental information comprises the steps of:

and superposing the drift probability distribution of the corresponding random particles on the electronic chart in different distress scenes to obtain the comprehensive drift probability distribution of the random particles on the electronic chart.

7. The method for determining a maritime search and rescue area according to claim 6, wherein before the step of calculating the drift velocity of a plurality of random particles corresponding to a scene in distress on the electronic chart according to the pre-stored environmental information and the wind pressure coefficient information corresponding to the search and rescue target, the method further comprises the following steps: prestoring the flow velocity of sea water surface layer ocean current, the wind speed 10 meters high from the sea surface, and a downwind direction wind speed slope coefficient, a downwind direction offset coefficient, a crosswind direction wind speed slope coefficient and a crosswind direction offset coefficient which are respectively corresponding to a search and rescue target in a distress scene and are 10 meters high from the sea surface; the step of calculating the drift velocity of a plurality of random particles corresponding to the distress scene on the electronic chart according to the pre-stored environmental information and the wind pressure coefficient information corresponding to the search and rescue target comprises the following steps:

calculating a downwind direction wind pressure vector according to the prestored wind speed 10 m high from the sea surface, and a downwind direction wind speed slope coefficient and a downwind direction offset coefficient which are respectively corresponding to the search and rescue target in the distress scene and are 10 m high from the sea surface, wherein the relationship among the wind speed 10 m high from the sea surface, the downwind direction wind speed slope coefficient, the downwind direction offset coefficient and the downwind direction wind pressure vector is satisfied：L_d=a_dW₁₀+b_dWherein W is₁₀The wind speed a is 10 m high from the sea surface_dThe slope coefficient of the wind speed in the downwind direction is 10 m high from the sea surface, b_dIs the downwind direction offset coefficient, L_dIs the wind pressure vector in the downwind direction;

and synthesizing the synthesized wind pressure vector and the prestored sea water surface layer current flow velocity vector to obtain the drift velocity of the plurality of random particles corresponding to the distress scene on the electronic chart.

8. The method for determining a maritime search and rescue area according to claim 7, wherein before the step of calculating the drift displacement of the plurality of random particles on the electronic chart corresponding to the scene in distress after the preset time according to the pre-stored environmental information, the method further comprises the following steps: prestoring the average flow velocity of ocean current with the depth of 0.5 m from the sea surface, the variance of flow velocity disturbance, the average value of wind speed with the height of 10 m from the sea surface, the variance of wind speed disturbance, and a downwind direction wind speed slope coefficient, a downwind direction offset coefficient, a crosswind direction wind speed slope coefficient, a crosswind direction offset coefficient and a variance of wind pressure coefficient disturbance which are respectively corresponding to search and rescue targets in a scene in danger and are 10 m from the sea surface; the step of calculating the drift displacement of a plurality of random particles on the electronic chart, corresponding to the distress scene after a preset time, according to the pre-stored environmental information comprises the following steps:

the average value of the wind speed 10 meters high from the sea surface is shown, u 'is the wind speed disturbance, the mean value of the wind speed disturbance u' is 0, and the wind speed disturbance variance is sigma_WRandomly extracting in the circular normal distribution;

calculating a downwind direction wind speed slope coefficient estimation value which is corresponding to a scene in danger and is 10 meters away from the sea surface according to the prestored downwind direction wind speed slope coefficient which is 10 meters away from the sea surface and the wind pressure coefficient disturbance, wherein the downwind direction wind speed slope coefficient which is 10 meters away from the sea surface, the wind pressure coefficient disturbance and the downwind direction wind speed slope coefficient estimation value which is 10 meters away from the sea surface satisfy the relationship: a is_1d＝a_d+ τ/20, wherein, a_1dIs the estimated value of the slope coefficient of the wind speed in the downwind direction 10 m away from the sea surface, wherein tau is the disturbance of the wind pressure coefficient, the mean value of the disturbance of the wind pressure coefficient tau is 0, and the disturbance variance of the wind pressure coefficient is sigma_LRandomly extracting in the circular normal distribution; calculating a downwind direction offset coefficient estimation value which is 10 meters away from the sea surface and corresponds to a scene in danger according to the downwind direction offset coefficient and the wind pressure coefficient disturbance which are prestored, wherein the downwind direction offset coefficient, the wind pressure coefficient disturbance and the downwind direction offset coefficient estimation value which is 10 meters away from the sea surface satisfy the relationship: b_1d＝b_d+ τ/2, wherein b_1dThe estimated value of the downwind direction offset coefficient is 10 meters away from the sea surface; according to the calculated wind speed slope in the downwind directionCalculating a coefficient estimated value, a downwind direction offset coefficient estimated value and a wind speed 10 meters away from the sea surface to obtain a downwind direction wind pressure vector;

calculating a crosswind direction wind speed slope coefficient estimation value which is 10 m away from the sea surface and corresponds to a scene in danger according to a prestored crosswind direction wind speed slope coefficient which is 10 m away from the sea surface and a prestored wind pressure coefficient disturbance, wherein the crosswind direction wind speed slope coefficient which is 10 m away from the sea surface, the wind pressure coefficient disturbance and the crosswind direction wind speed slope coefficient estimation value which is 10 m away from the sea surface satisfy the relationship: a is_1c＝a_c+ τ/20, wherein, a_1cThe estimated value of the slope coefficient of the wind speed in the crosswind direction is 10 meters away from the sea surface; calculating a crosswind direction offset coefficient estimation value which is 10 m high from the sea surface and corresponds to a scene in danger according to a prestored crosswind direction offset coefficient and a prestored wind pressure coefficient disturbance, wherein the crosswind direction offset coefficient, the wind pressure coefficient disturbance and the crosswind direction offset coefficient estimation value which is 10 m high from the sea surface satisfy the relationship: b_1c＝b_c+ τ/2, wherein b_1cThe cross wind direction offset coefficient estimation value is 10 m high from the sea surface; calculating to obtain a crosswind direction wind pressure vector according to the calculated crosswind direction wind speed slope coefficient estimated value, crosswind direction offset coefficient estimated value and the wind speed 10 meters away from the sea surface;

wherein,

the average current velocity at a depth of 0.5 m from the sea surface, w' is the current disturbance fromMean 0, disturbance variance σ_CRandomly extracting in the circular normal distribution;

according to the synthesized wind pressure vector and the calculated sea water surface layer ocean current flow velocity, calculating the drift displacement of a plurality of random particles on the electronic chart corresponding to a distress scene after a preset time, wherein the wind pressure vector, the sea water surface layer ocean current flow velocity and the drift displacement of the plurality of random particles on the electronic chart satisfy the following relations:

wherein S (t) is the position of the random particles on the electronic chart after a preset time, S₀Initial positions of random particles on the electronic chart, S (t) -S₀The method is characterized in that the drift displacement of random particles on the electronic chart is shown, t is preset drift time, C (t) is flow velocity of sea water surface current, L (t) is a wind pressure vector, V (t ') is drift velocity of a search and rescue target at t ', t ' is an integral variable, the integral lower limit of t ' is 0, and the integral upper limit of t ' is t.

9. A system for determining a maritime search and rescue area, the system comprising:

10. A search and rescue simulator, comprising a system for determining a maritime search and rescue area, the system for determining a maritime search and rescue area comprising: