Cosmic ray ground space positioning method and device, electronic equipment and storage medium

Abstract

The invention relates to a cosmic ray ground space positioning method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the actual measurement muon flux of a to-be-positioned target location, the actual measurement muon flux being detected by a cosmic ray muon detection system located at the target location; determining a position distribution mapping relation according to the flux detection area and the flux detection duration of the cosmic ray muon detection system and a preset position flux mapping relation; wherein the position flux mapping relation represents the mapping relation from different longitudes and latitudes to theoretical muon flux in the global range, and the position distribution mapping relation represents the mapping relation from different longitudes and latitudes to actual measurement muon flux probability distribution in the global range; and determining a target latitude and longitude corresponding to the target location according to the actually measured muon flux and the position distribution mapping relation. Therefore, the longitude and latitude are reversely deduced by measuring the muon flux by utilizing the non-uniformity of the ground muon flux in the spatial position, so that the spatial positioning is realized.

Description

Technical Field

[0001] The present disclosure relates to the field of nuclear technology, and in particular to a method and device for ground-based space positioning of cosmic rays, electronic equipment, and storage medium. Background Art

[0002] The spatial position on the surface of the earth can usually be obtained by using global satellite positioning systems, such as the Beidou satellite navigation system, the Global Positioning System, the GLONASS satellite navigation system, and the Galileo satellite navigation system. In places where telecommunications are developed, spatial positioning can also be obtained through communication base stations. The above positioning systems basically rely on electromagnetic wave communications. However, in some scenarios, electromagnetic waves may be interfered or blocked. For example, in positioning scenarios such as underwater and underground, it will be difficult to rely on electromagnetic waves to carry out communication positioning. Therefore, the development of a positioning system that does not rely on electromagnetic wave communications has become a potential demand.

[0003] It is known that high-energy cosmic rays from outer space interact with the atmosphere, and showers occur in the atmosphere, producing a large number of secondary particles (i.e., cosmic ray muons). These secondary particles reach the surface of the earth and form secondary cosmic rays. Due to the influence of the earth's magnetic field, the intensity of cosmic ray particles reaching the surface of the earth at different longitudes and latitudes (i.e., muon flux) is different, and cosmic ray muons have strong penetrability and are easy to detect. Therefore, using cosmic ray muon flux to achieve spatial positioning that does not rely on electromagnetic wave communication has become a development trend. Summary of the invention

[0004] In view of this, the present disclosure proposes a cosmic ray ground space positioning method and device, electronic equipment and storage medium, which can utilize the unevenness of the ground muon flux in spatial position, and reversely infer the longitude and latitude by measuring the muon flux, thereby achieving spatial positioning.

[0005] According to one aspect of the present disclosure, a spatial positioning method is provided, comprising: obtaining a measured muon flux of a target location to be positioned, wherein the measured muon flux is detected by a cosmic ray muon detection system located at the target location; determining a position distribution mapping relationship according to a flux detection area and a flux detection duration of the cosmic ray muon detection system and a preset position flux mapping relationship; wherein the position flux mapping relationship represents a mapping relationship from different longitudes and latitudes in a global scope to theoretical muon fluxes, and the position distribution mapping relationship represents a mapping relationship from different longitudes and latitudes in a global scope to a measured muon flux probability distribution, and the measured muon flux probability distribution at any longitude and latitude represents the probability distribution obeyed by the muon flux detected by the cosmic ray muon detection system at the longitude and latitude; and determining the target longitude and latitude corresponding to the target location according to the measured muon flux and the muon flux probability distribution.

[0006] In a possible implementation, determining the target longitude and latitude corresponding to the target location according to the measured muon flux and the position distribution mapping relationship includes: determining the posterior distribution of longitude and latitude based on Bayesian inference based on the measured muon flux, the position distribution mapping relationship and a preset longitude and latitude prior distribution; wherein the longitude and latitude prior distribution includes the prior probabilities corresponding to different longitudes and latitudes in a global scope; the longitude and latitude posterior distribution includes the posterior probabilities corresponding to different longitudes and latitudes in a global scope given the measured muon flux; and determining the target longitude and latitude corresponding to the target location according to the posterior distribution of longitude and latitude corresponding to the target location.

[0007] In a possible implementation, the target longitude and latitude include the longitude and latitude that maximize the posterior probability in the posterior distribution of the longitude and latitude; the posterior distribution of the longitude and latitude is expressed as:

[0008]

[0009] Among them, p represents longitude and latitude, f represents the measured muon flux, g(f|p) represents the position distribution mapping relationship, g(p) represents the longitude and latitude prior distribution, ∫g(f|p)g(p)dp represents the integral of the product of g(f|p) and g(p) over the global longitude and latitude, and g(p|f) represents the longitude and latitude posterior distribution.

[0010] In a possible implementation, the latitude and longitude prior distribution includes a uniform distribution; when the latitude and longitude prior distribution is a uniform distribution, the latitude and longitude posterior distribution is expressed as:

[0011]

[0012] In one possible implementation, the position distribution mapping relationship includes a Gaussian distribution, the expectation corresponding to the Gaussian distribution is determined based on the position flux mapping relationship, and the variance corresponding to the Gaussian distribution is determined based on the position flux mapping relationship, the flux detection area and the flux detection duration; the position flux mapping relationship is expressed as a function with longitude and latitude as independent variables and theoretical muon flux as dependent variable.

[0013] In one possible implementation, the method further includes: determining a likelihood region area based on the target longitude and latitude, the likelihood region area including the area of ​​a geographical region centered on the target longitude and latitude and whose sum of posterior probabilities is a specified value; and determining the ratio of the likelihood region area to the total area of ​​the earth's surface as the positioning accuracy corresponding to the target longitude and latitude.

[0014] In a possible implementation, the cosmic ray muon detection system includes multiple cosmic ray muon detectors, the cosmic ray muon detectors include plastic scintillator detectors, and the measured muon flux is the muon flux determined based on detection signals corresponding to muon events passing through all cosmic ray muon detectors in the cosmic ray muon detection system.

[0015] According to another aspect of the present disclosure, a space positioning device is provided, including: an acquisition module, used to acquire the measured muon flux of a target location to be positioned, wherein the measured muon flux is detected by a cosmic ray muon detection system located at the target location; a probability distribution determination module, used to determine a position distribution mapping relationship according to a flux detection area and a flux detection duration of the cosmic ray muon detection system and a preset position flux mapping relationship; wherein the position flux mapping relationship represents a mapping relationship from different longitudes and latitudes in a global scope to theoretical muon fluxes, and the position distribution mapping relationship represents a mapping relationship from different longitudes and latitudes in a global scope to the measured muon flux probability distribution, and the measured muon flux probability distribution at any longitude and latitude represents the probability distribution obeyed by the muon flux detected by the cosmic ray muon detection system at the longitude and latitude; and a longitude and latitude determination module, used to determine the target longitude and latitude corresponding to the target location according to the measured muon flux and the position distribution mapping relationship.

[0016] In one possible implementation, the device also includes: a region area determination module, used to determine the likelihood region area based on the target longitude and latitude, the likelihood region area including the region area of ​​a geographical region centered on the target longitude and latitude and whose sum of posterior probabilities is a specified value; a positioning accuracy determination module, used to determine the ratio between the likelihood region area and the total area of ​​the earth's surface as the positioning accuracy corresponding to the target longitude and latitude.

[0017] According to another aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0018] According to another aspect of the present disclosure, a non-volatile computer-readable storage medium is provided, on which computer program instructions are stored, wherein the computer program instructions implement the above method when executed by a processor.

[0019] According to another aspect of the present disclosure, a computer program product is provided, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above method.

[0020] According to the embodiments of the present disclosure, the target longitude and latitude of the target location are determined by obtaining the measured muon flux of the target location to be located, and combining the position distribution mapping relationship determined by the flux detection area and flux detection duration of the cosmic ray muon detection system with a preset position flux mapping relationship. This allows the use of the unevenness of the ground muon flux in spatial position to reversely infer the longitude and latitude by measuring the measured muon flux of any target location, thereby achieving spatial positioning of any location.

[0021] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0023] Figure 1 A schematic diagram showing predicted values ​​of surface muon flux for different geomagnetic cutoff stiffnesses according to an embodiment of the present disclosure.

[0024] Figure 2 A schematic diagram showing the geomagnetic cutoff stiffness at different longitudes and latitudes around the world according to an embodiment of the present disclosure.

[0025] Figure 3 A schematic diagram showing theoretical muon fluxes at different longitudes and latitudes around the world according to an embodiment of the present disclosure.

[0026] Figure 4 A flow chart of a spatial positioning method according to an embodiment of the present disclosure is shown.

[0027] Figure 5 A schematic diagram of a cosmic ray muon detection system according to an embodiment of the present disclosure is shown.

[0028] Figure 6 A distribution diagram of a posterior distribution of longitude and latitude according to an embodiment of the present disclosure is shown.

[0029] Figure 7 A schematic diagram showing positioning accuracy at different longitudes and latitudes around the world according to an embodiment of the present disclosure.

[0030] Figure 8 A block diagram of a space positioning device according to an embodiment of the present disclosure is shown.

[0031] Fig. 9 A block diagram of an electronic device 1900 according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0032] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0033] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0034] The term "and / or" herein is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C can represent including any one or more elements selected from the set consisting of A, B, and C.

[0035] The terms “include” and “comprising” used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0036] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present disclosure.

[0037] In practical applications, the spatial positioning method proposed in the embodiment of the present disclosure can be deployed on various terminal devices through software or hardware modification. The terminal device involved in the embodiment of the present disclosure may refer to a device with a wireless connection function and / or a wired connection function. The wireless connection function refers to the ability to connect to other devices through wireless connection methods such as wifi and Bluetooth. The terminal device involved in the embodiment of the present disclosure may also communicate with other devices through a wired connection function. The terminal device involved in the embodiment of the present disclosure may be a touch screen, a non-touch screen, or a screenless device. The touch screen device can be controlled by clicking and sliding on the display screen with a finger or a stylus. The non-touch screen device can be connected to an input device such as a mouse, a keyboard, a touch panel, and the terminal device is controlled through the input device. For example, the device without a screen may be a Bluetooth speaker without a screen. For example, the terminal device of the present application may include but is not limited to a user equipment (UE), a mobile device, a user terminal, a terminal, a handheld device, a tablet computer, a laptop, a PDA, a computing device, etc.

[0038] The spatial positioning method of the embodiment of the present disclosure can also be deployed on a server, which can be located in the cloud or locally, and can be a physical device or a virtual device, such as a virtual machine, a container, etc., with a wireless communication function, wherein the wireless communication function can be set in the chip (system) or other parts or components of the server. It can refer to a device with a wireless connection function, and the function of wireless connection refers to the ability to connect to other servers or terminal devices through wireless connection methods such as Wi-Fi and Bluetooth. The server involved in the embodiment of the present disclosure may also have the function of communicating through a wired connection. For example, the server can receive the measured muon flux of the target location sent by the terminal device, and the server executes the spatial positioning method of the embodiment of the present disclosure based on the measured muon flux, obtains the target longitude and latitude of the target location, and returns the target longitude and latitude to the terminal device, so as to provide the user with the spatial positioning result of the target location in the terminal device.

[0039] To facilitate understanding of the spatial positioning method realized by utilizing the cosmic ray muon flux proposed in the embodiments of the present disclosure, this article first introduces the theoretical basis involved in the spatial positioning method as follows: It can be seen that the blocking of cosmic rays by the earth's magnetic field can be expressed by the geomagnetic cutoff rigidity. The larger the geomagnetic cutoff rigidity, the smaller the flux of primary cosmic rays, which makes the surface muon flux smaller, and vice versa. The inhomogeneity of the surface geomagnetic cut-off rigidity leads to the inhomogeneity of muons. Any position on the earth's surface is irradiated by natural cosmic ray muons at any time, and there is inhomogeneity in the muon flux at different positions, especially in the latitudinal direction. For example, Figure 1 The predicted values ​​of the surface muon flux for different geomagnetic cutoff stiffnesses are shown in Figure 2. Figure 1 It can be seen that when the geomagnetic cutoff stiffness increases from 0 GV (at the geomagnetic poles) to 15 GV (near the geomagnetic equator), the muon flux increases from 0.69 cm -2 s -1 Down to 0.59cm -2 s -1 It can be seen that the muon flux is very sensitive to the size of the geomagnetic cutoff stiffness, and it is theoretically feasible to use the measurement of cosmic ray muon flux to locate in space (latitude). On this basis, Figure 2 It is shown that according to the latitude and longitude, a grid point is obtained every one degree, and the geomagnetic cutoff stiffness of different longitudes and latitudes around the world is calculated, which can be used according to Figure 1 The obtained relationship between the geomagnetic cutoff stiffness and the muon flux is combined with Figure 2 The relationship between the global geomagnetic cutoff stiffness and longitude and latitude is shown, and further obtained as Figure 3 The theoretical muon flux at different longitudes and latitudes around the world is shown (one point is obtained every 1 degree of longitude and latitude), which is the theoretical result of the global muon flux. Figure 3 It can be seen that the muon flux varies greatly not only in latitude, but also in longitude. This proves that it is theoretically feasible to locate the spatial position (latitude and longitude) by measuring the muon flux of cosmic rays on the ground. Based on the above theoretical basis, the embodiment of the present disclosure proposes a spatial positioning method by measuring the muon flux of cosmic rays at any location and inferring the longitude and latitude of the location in turn.

[0040] Figure 4 FIG. 1 is a flow chart showing a spatial positioning method according to an embodiment of the present disclosure. The method can be applied to electronic devices such as the above-mentioned terminal device or server. Figure 4 As shown, the method includes: step S11 to step S13.

[0041] In step S11, the measured muon flux of the target location to be located is obtained, and the measured muon flux is detected by a cosmic ray muon detection system located at the target location.

[0042] In practical applications, those skilled in the art can use any existing cosmic ray muon detection system in the art to detect the muon flux of any target location to be located and obtain the measured muon flux of the target location, which is not limited to the embodiments of the present disclosure.

[0043] In a possible implementation, the cosmic ray muon detection system may include multiple cosmic ray muon detectors, which may include plastic scintillator detectors. That is, the cosmic ray muon detection system may use a plastic scintillator detector array, wherein a single plastic scintillator detector is mainly composed of a plastic scintillator and a SiPM (Silicon photomultiplier) array, a power module, a comparator, and the like, which can realize sensitive detection of the two-dimensional position of muons. For example, a detection area of ​​1024 cm 2 , a plastic scintillator detector with a position resolution of about 0.5 cm and a single module geometric acceptance of about 85.41%. Figure 5 As shown, for the measurement of the surface muon flux, a plurality of cosmic ray muon detectors (01, 02, 03 and 04) can be used to form a cosmic ray muon detection system to achieve accurate measurement of the cosmic ray muon flux.

[0044] It can be known that muon is a particle with extremely strong penetrability. Muon events can be screened by multi-layer detector coincidence to achieve the measurement of muon flux. That is, the plastic scintillator detector and coincidence technology can be used to measure the muon flux in the cosmic rays at the target location. Specifically, based on the strong penetrating properties of muons, multiple coincident muon events that pass through all detectors in the detection system can be screened out to achieve the measurement of muon flux. It can be known that the working principle of the plastic scintillator detector is: charged particles cause ionization excitation in the plastic scintillator, generating fluorescent photons, which are captured by the photocathode of the silicon photomultiplier tube and emit photoelectrons. The photoelectrons are multiplied under the action of the electric field, and finally a detection signal (i.e., an electrical signal) is generated in the output circuit to achieve the detection of the muon flux. Therefore, the measured muon flux can be the muon flux determined based on the muon events that pass through all cosmic ray muon detectors in the cosmic ray muon detection system. Specifically, the detection signal generated by the muon events that pass through all cosmic ray muon detectors can be screened out, and then the measured muon flux is determined based on the detection signal.

[0045] In step S12, the position distribution mapping relationship is determined according to the flux detection area and flux detection duration of the cosmic ray muon detection system and a preset position flux mapping relationship.

[0046] Among them, the flux detection area of ​​the cosmic ray muon detection system can be understood as the effective detection area of ​​a single cosmic ray muon detector in the detection system, and the flux detection duration can be understood as the duration of detecting the muon flux at the target location using the cosmic ray muon detection system. It should be understood that the effective detection area depends on the hardware characteristics of the cosmic ray muon detector, and the flux detection duration can be determined according to actual needs. For example, muon flux detection can be performed at the target location for multiple days, and then the measured muon flux at the target location can be obtained based on the muon flux detection results for multiple days. The embodiments of the present disclosure do not limit this.

[0047] Among them, the position flux mapping relationship represents the mapping relationship between different longitudes and latitudes in the global range and the theoretical muon flux. It should be understood that those skilled in the art can use any known technical means in the art to obtain the theoretical muon flux corresponding to any longitude and latitude in the global range, and the embodiments of the present disclosure are not limited to this. Figure 3 The global muon flux theoretical results shown can be determined as a position flux mapping relationship, wherein the position flux mapping relationship can be expressed as a function with longitude and latitude as independent variables and theoretical muon flux as dependent variable, so as to facilitate the subsequent calculation of the position distribution mapping relationship.

[0048] It should be understood that the theoretical muon flux at a given longitude and latitude is a fixed value and has no distribution. However, since there is an error (i.e., fluctuation) when the cosmic ray muon detection system measures the muon flux, there is a distribution. Therefore, the flux detection area and flux detection duration of the cosmic ray muon detection system and the preset position flux mapping relationship can be used to determine the position distribution mapping relationship produced by the measurement error of the cosmic ray muon detection system, wherein the position distribution mapping relationship represents the mapping relationship between different longitudes and latitudes in the global range and the measured muon flux probability distribution. The measured muon flux probability distribution at any longitude and latitude represents the probability distribution obeyed by the muon flux detected by the cosmic ray muon detection system at the longitude and latitude, that is, the position distribution mapping relationship includes the mapping relationship between each longitude and latitude in the global range and the probability distribution obeyed by the muon flux detected by the cosmic ray muon detection system at the longitude and latitude.

[0049] Optionally, since there is a statistical fluctuation (i.e., statistical error) in the muon flux F in actual measurement, when the flux measurement duration and the flux detection area are large enough, for example, the flux measurement duration can be made to reach 100 days, etc., the mapping relationship between any longitude and latitude and the probability distribution of the muon flux measured at the longitude and longitude can be approximated by a Gaussian distribution, that is, the position distribution mapping relationship can include a Gaussian distribution, wherein the longitude and latitude of the target location P is assumed to be (p lat ,p long), the flux detection area of ​​the cosmic ray muon detection system is s, and the flux detection time is t. The muon flux detected at any location is F, and the expectation of F is E(F) = E(F|p lat ,p long ), where the expectation of the measured muon flux at any location can be considered to be the theoretical muon flux at that location, then E(F) can be expressed as Figure 3 The theoretical results of the global muon flux are presented, which can be a position flux mapping relationship in the form of a function.

[0050] For example, the position distribution mapping relationship g(f|p) can be expressed as formula (1):

[0051]

[0052] Where p represents longitude and latitude, and f represents the muon flux detected by the cosmic ray muon detection system. From formula (1), it can be seen that the Gaussian distribution The corresponding expectation E(F) is determined based on the position flux mapping relationship, and the variance corresponding to the Gaussian distribution is It is determined based on the position flux mapping relationship, the flux detection area s and the flux detection time t.

[0053] It should be understood that using Gaussian distribution to approximate the above-mentioned position distribution mapping relationship is a possible implementation method proposed in the embodiment of the present disclosure. In fact, under the guidance of the embodiment of the present disclosure, those skilled in the art can also adopt a probability distribution model of a type known in the art to obtain the above-mentioned position distribution mapping relationship, and the embodiment of the present disclosure does not limit this.

[0054] In step S13, the target longitude and latitude corresponding to the target location are determined according to the measured muon flux and the position distribution mapping relationship.

[0055] In practical applications, for example, estimation methods such as maximum likelihood estimation can be used to find the longitude and latitude with the highest probability of having the measured muon flux detected at the target location based on the position distribution mapping relationship as the target longitude and latitude corresponding to the target location. Of course, other probability estimation methods known in the art can also be used to infer the longitude and latitude with the highest probability of having the measured muon flux detected at the target location, and the embodiments of the present disclosure are not limited to this.

[0056] In a possible implementation, the posterior distribution of longitude and latitude under a given flux detection result (i.e., a given measured muon flux) can be obtained based on Bayesian inference combined with the position distribution mapping relationship, and then the target longitude and latitude can be inferred based on the posterior distribution of longitude and latitude and the principle of maximum likelihood estimation, that is, the target longitude and latitude can include the longitude and latitude that maximizes the posterior probability in the posterior distribution of longitude and latitude. Therefore, the above-mentioned determination of the target longitude and latitude corresponding to the target location based on the measured muon flux and the position distribution mapping relationship can include:

[0057] Based on the measured muon flux, the mapping relationship between the position distribution and the preset longitude and latitude prior distribution, the longitude and latitude posterior distribution based on Bayesian inference is determined; wherein the longitude and latitude prior distribution includes the prior probabilities corresponding to different longitudes and latitudes in the world; the longitude and latitude posterior distribution includes the posterior probabilities corresponding to different longitudes and latitudes in the world under the given measured muon flux;

[0058] According to the posterior distribution of the longitude and latitude corresponding to the target location, the target longitude and latitude corresponding to the target location are determined.

[0059] Among them, the posterior distribution of longitude and latitude based on Bayesian inference can be expressed as formula (2):

[0060]

[0061] Among them, p represents longitude and latitude, f represents the measured muon flux, g(f|p) represents the position distribution mapping relationship, g(p) represents the prior distribution of longitude and latitude, g(f) represents the total probability corresponding to the longitude and latitude on the global scale, ∫g(f|p)g(p)dp represents the integral of the product of g(f|p) and g(p) over the longitude and latitude on the global scale, and g(p|f) represents the posterior distribution of longitude and latitude.

[0062] In practical applications, the prior probabilities corresponding to different longitudes and latitudes in the global range can be preset based on prior knowledge such as empirical rules or measurement information, that is, the prior distribution of longitudes and latitudes can be preset. Optionally, if there is no other prior knowledge about longitudes and latitudes, the prior distribution of longitudes and latitudes can be set to uniform distribution. When the prior distribution of longitudes and latitudes is uniform distribution, the posterior distribution of longitudes and latitudes can be expressed as formula (3):

[0063]

[0064] Where ∫g(f|p)dp represents the integral of g(f|p) over the longitude and latitude of the entire globe. In practical applications, after obtaining the measured muon flux f at the target location, it can be substituted into the above formula (2) or formula (3) to obtain the posterior distribution of longitude and latitude based on Bayesian inference.

[0065] After obtaining the above latitude and longitude posterior distribution, the maximum likelihood estimation method can be used to find the latitude and longitude that maximizes the posterior probability in the latitude and longitude posterior distribution, that is, to infer the target latitude and longitude of the target location. The embodiment of the present disclosure does not limit the reasoning process of determining the target latitude and longitude using the maximum likelihood estimation method.

[0066] According to the embodiments of the present disclosure, the target longitude and latitude of the target location are determined by obtaining the measured muon flux of the target location to be located, and combining the position distribution mapping relationship determined by the flux detection area and flux detection duration of the cosmic ray muon detection system with a preset position flux mapping relationship. This allows the use of the unevenness of the ground muon flux in spatial position to reversely infer the longitude and latitude by measuring the measured muon flux of any target location, thereby achieving spatial positioning of any location.

[0067] Considering that there are errors in the measurement results of the cosmic ray muon flux measured by the cosmic ray muon detection system, the target longitude and latitude finally inferred may also have errors. Therefore, in a possible implementation, the characteristics of Bayesian inference can also be combined to give the possible two-dimensional longitude and latitude regional distribution after giving the most likely target longitude and latitude, and then give the positioning accuracy of the target longitude and latitude. Specifically, the method can also include:

[0068] Based on the target longitude and latitude, determine the likelihood area (One-Sigma-Equivalent-Area, OSEA), which includes the area of ​​the geographical area centered on the target longitude and latitude and whose posterior probability sum is a specified value;

[0069] The ratio between the area of ​​the likelihood region and the total area of ​​the earth's surface is determined as the positioning accuracy corresponding to the target longitude and latitude.

[0070] Among them, the specified value can be, for example, the area "68.3%" within the horizontal axis interval (μ-σ, μ+σ) in the Gaussian distribution, that is, the likelihood region area can be defined as "the area of ​​the geographical area centered on the target longitude and latitude of maximum likelihood and the sum of the posterior probabilities is 68.3%". Of course, other values ​​can also be used. Those skilled in the art can set the above specified values ​​according to actual needs, and the embodiments of the present disclosure are not limited to this. It should be understood that, given the posterior probabilities corresponding to different longitudes and latitudes in the global range under a given measured muon flux, the geographical area defined by the longitude and latitude centered on the target longitude and latitude of maximum likelihood and the sum of the posterior probabilities is 68.3% can be found, and the likelihood region area can be obtained, and then the positioning accuracy ∈ corresponding to the target location can be defined as the ratio of the likelihood region area to the total surface area of ​​the earth.

[0071] Among them, the likelihood area OSEA can be expressed as formula (4), and the positioning accuracy ∈ can be expressed as formula (5):

[0072]

[0073] Among them, Ω0 represents the geographical area centered on the target latitude and longitude of maximum likelihood and with a posterior probability sum of 68.3%; Ω represents the entire area of ​​the earth's surface, S Earth Represents the total surface area of ​​the Earth.

[0074] It should be understood that the smaller the positioning accuracy ∈, the more accurate the positioning is, ranging from 0 to 1. When there is no positioning capability at all, ∈=1; when there is no positioning error in the longitude and latitude, ∈=0. By providing the positioning accuracy corresponding to the target longitude and latitude, users can obtain more positioning information.

[0075] In practical applications, after obtaining the posterior distribution of longitude and latitude corresponding to the target location, a visual posterior distribution map of longitude and latitude can be generated. At the same time, the inferred target longitude and latitude, positioning accuracy and the posterior distribution map of longitude and latitude can be displayed to the user, which can provide a reference for the user's actual spatial positioning, so that the user can obtain accurate positioning results.

[0076] For example, taking the target location to be located (40°N, 120°E) as an example, the theoretical muon flux at this location is 0.66 cm -2 min -1 , assuming that the flux detection area of ​​the cosmic ray muon detection system is s = 1m 2 , the flux detection duration is t = 1 day (d), that is, the measured exposure is 1m 2 ×d, through the above steps S11 to S12, the following can be obtained: Figure 6 The distribution diagram of the posterior distribution of longitude and latitude shown in FIG. 1 can then refer to the above step S13 to use the maximum likelihood estimation based on Figure 6 The target longitude and latitude are inferred from the posterior distribution of the longitude and latitude shown. Then, the positioning accuracy ∈≈0.00146 corresponding to the target longitude and latitude can be calculated based on the target longitude and latitude with reference to the calculation process of the positioning accuracy mentioned above. Therefore, the possible position range of the surface can be reduced by about 700 times through the muon positioning accuracy.

[0077] Figure 7 It is shown that s = 1m 2 , the positioning accuracy of different longitudes and latitudes around the world calculated by the cosmic ray muon detection system at t = 24d is given by Figure 7 It can be found that the distribution of positioning accuracy is very similar to the shape of muon flux distribution. In low-latitude areas, the muon positioning accuracy is higher; in high-latitude areas, the muon positioning accuracy is lower.

[0078] Figure 8 A block diagram of a spatial positioning device according to an embodiment of the present disclosure is shown as follows: Figure 8As shown, the device comprises:

[0079] An acquisition module 801 is used to acquire a measured muon flux of a target location to be located, wherein the measured muon flux is detected by a cosmic ray muon detection system located at the target location;

[0080] The probability distribution determination module 802 is used to determine the position distribution mapping relationship according to the flux detection area and flux detection duration of the cosmic ray muon detection system and the preset position flux mapping relationship; wherein the position flux mapping relationship represents the mapping relationship from different longitudes and latitudes in the global range to the theoretical muon flux, and the position distribution mapping relationship represents the mapping relationship from different longitudes and latitudes in the global range to the measured muon flux probability distribution, and the measured muon flux probability distribution at any longitude and latitude represents the probability distribution obeyed by the muon flux detected by the cosmic ray muon detection system at the longitude and latitude;

[0081] The longitude and latitude determination module 803 is used to determine the target longitude and latitude corresponding to the target location according to the measured muon flux and the position distribution mapping relationship.

[0082] In a possible implementation, determining the target longitude and latitude corresponding to the target location according to the measured muon flux and the position distribution mapping relationship includes: determining the posterior distribution of longitude and latitude based on Bayesian inference based on the measured muon flux, the position distribution mapping relationship and a preset longitude and latitude prior distribution; wherein the longitude and latitude prior distribution includes the prior probabilities corresponding to different longitudes and latitudes in a global scope; the longitude and latitude posterior distribution includes the posterior probabilities corresponding to different longitudes and latitudes in a global scope given the measured muon flux; and determining the target longitude and latitude corresponding to the target location according to the posterior distribution of longitude and latitude corresponding to the target location.

[0083] In a possible implementation, the target longitude and latitude include the longitude and latitude that maximize the posterior probability in the posterior distribution of the longitude and latitude; the posterior distribution of the longitude and latitude is expressed as:

[0084]

[0085] Among them, p represents longitude and latitude, f represents the measured muon flux, g(f|p) represents the probability distribution of the measured muon flux, g(p) represents the prior distribution of longitude and latitude, ∫g(f|p)g(p)dp represents the integral of the product of g(f|p) and g(p) over the global longitude and latitude, and g(p|f) represents the posterior distribution of longitude and latitude.

[0086] In a possible implementation, the latitude and longitude prior distribution includes a uniform distribution; when the latitude and longitude prior distribution is a uniform distribution, the latitude and longitude posterior distribution is expressed as:

[0087]

[0088] In one possible implementation, the position distribution mapping relationship includes a Gaussian distribution, the expectation corresponding to the Gaussian distribution is determined based on the position flux mapping relationship, and the variance corresponding to the Gaussian distribution is determined based on the position flux mapping relationship, the flux detection area and the flux detection duration; the position flux mapping relationship is expressed as a function with longitude and latitude as independent variables and theoretical muon flux as dependent variable.

[0089] In one possible implementation, the device also includes: a region area determination module, used to determine the likelihood region area based on the target longitude and latitude, the likelihood region area including the region area of ​​a geographical region centered on the target longitude and latitude and whose sum of posterior probabilities is a specified value; a positioning accuracy determination module, used to determine the ratio between the likelihood region area and the total area of ​​the earth's surface as the positioning accuracy corresponding to the target longitude and latitude.

[0090] In a possible implementation, the cosmic ray muon detection system includes multiple cosmic ray muon detectors, the cosmic ray muon detectors include plastic scintillator detectors, and the measured muon flux is the muon flux determined based on detection signals corresponding to muon events passing through all cosmic ray muon detectors in the cosmic ray muon detection system.

[0091] According to the embodiments of the present disclosure, the target longitude and latitude of the target location are determined by obtaining the measured muon flux of the target location to be located, and combining the position distribution mapping relationship determined by the flux detection area and flux detection duration of the cosmic ray muon detection system with a preset position flux mapping relationship. This allows the use of the unevenness of the ground muon flux in spatial position to reversely infer the longitude and latitude by measuring the measured muon flux of any target location, thereby achieving spatial positioning of any location.

[0092] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0093] The embodiment of the present disclosure also provides a computer-readable storage medium on which computer program instructions are stored, and the computer program instructions implement the above method when executed by a processor. The computer-readable storage medium can be a volatile or non-volatile computer-readable storage medium.

[0094] An embodiment of the present disclosure further proposes an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0095] The embodiments of the present disclosure also provide a computer program product, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above method.

[0096] Fig. 9 1 is a block diagram of an electronic device 1900 according to an embodiment of the present disclosure. For example, the electronic device 1900 may be provided as a server or a terminal device. Fig. 9 , the electronic device 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932 for storing instructions executable by the processing component 1922, such as an application. The application stored in the memory 1932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute instructions to perform the above method.

[0097] The electronic device 1900 may also include a power supply component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input / output interface 1958 (I / O interface). The electronic device 1900 may operate based on an operating system stored in the memory 1932, such as Windows Server 2003. TM , Mac OS X TM , Unix TM ,Linux TM , FreeBSD TM or similar.

[0098] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions, which can be executed by the processing component 1922 of the electronic device 1900 to perform the above method.

[0099] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0100] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0101] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0102] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0103] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0104] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0105] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0106] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

[0107] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A spatial positioning method, characterized in that: include: Acquiring a measured muon flux of a target location to be located, wherein the measured muon flux is detected by a cosmic ray muon detection system located at the target location; According to the flux detection area and flux detection duration of the cosmic ray muon detection system and the preset position flux mapping relationship, the position distribution mapping relationship is determined; wherein the position flux mapping relationship represents the mapping relationship from different longitudes and latitudes in the global range to the theoretical muon flux, and the position distribution mapping relationship represents the mapping relationship from different longitudes and latitudes in the global range to the measured muon flux probability distribution, and the measured muon flux probability distribution at any longitude and latitude represents the probability distribution obeyed by the muon flux detected by the cosmic ray muon detection system at the longitude and latitude; The target longitude and latitude corresponding to the target location are determined according to the measured muon flux and the position distribution mapping relationship.

2. The method according to claim 1, characterized in that: Determining the target longitude and latitude corresponding to the target location according to the measured muon flux and the position distribution mapping relationship includes: Based on the measured muon flux, the position distribution mapping relationship and the preset longitude and latitude prior distribution, determine the longitude and latitude posterior distribution based on Bayesian inference; wherein the longitude and latitude prior distribution includes the prior probabilities corresponding to different longitudes and latitudes in the global range; the longitude and latitude posterior distribution includes the posterior probabilities corresponding to different longitudes and latitudes in the global range given the measured muon flux; The target longitude and latitude corresponding to the target location are determined according to the posterior distribution of the longitude and latitude corresponding to the target location.

3. The method according to claim 2, characterized in that The target longitude and latitude include the longitude and latitude that maximize the posterior probability in the posterior distribution of the longitude and latitude; The posterior distribution of longitude and latitude is expressed as: Among them, p represents longitude and latitude, f represents the measured muon flux, g(f|p) represents the position distribution mapping relationship, g(p) represents the longitude and latitude prior distribution, ∫g(f|p)g(p)dp represents the integral of the product of g(f|p) and g(p) over the global longitude and latitude, and g(p|f) represents the longitude and latitude posterior distribution.

4. The method according to claim 3, characterized in that The latitude and longitude prior distribution includes a uniform distribution; when the latitude and longitude prior distribution is a uniform distribution, the latitude and longitude posterior distribution is expressed as:

5. The method according to claim 1, characterized in that The position distribution mapping relationship includes a Gaussian distribution, the expectation corresponding to the Gaussian distribution is determined based on the position flux mapping relationship, and the variance corresponding to the Gaussian distribution is determined based on the position flux mapping relationship, the flux detection area, and the flux detection duration; The position flux mapping relationship is expressed as a function with longitude and latitude as independent variables and theoretical muon flux as dependent variable.

6. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: Based on the target longitude and latitude, determining a likelihood region area, wherein the likelihood region area includes a region area of ​​a geographical region centered on the target longitude and latitude and having a sum of posterior probabilities equal to a specified value; The ratio of the area of ​​the likelihood region to the total area of ​​the earth's surface is determined as the positioning accuracy corresponding to the target longitude and latitude.

7. The method according to any one of claims 1 to 5, characterized in that: The cosmic ray muon detection system includes a plurality of cosmic ray muon detectors, and the cosmic ray muon detectors include plastic scintillator detectors. The measured muon flux is the muon flux determined based on muon events passing through all cosmic ray muon detectors in the cosmic ray muon detection system.

8. A spatial positioning device, characterized in that: include: An acquisition module, used for acquiring a measured muon flux of a target location to be located, wherein the measured muon flux is detected by a cosmic ray muon detection system located at the target location; A probability distribution determination module, for determining a position distribution mapping relationship according to the flux detection area and flux detection duration of the cosmic ray muon detection system and a preset position flux mapping relationship; wherein the position flux mapping relationship represents a mapping relationship from different longitudes and latitudes in the global range to theoretical muon fluxes, and the position distribution mapping relationship represents a mapping relationship from different longitudes and latitudes in the global range to the measured muon flux probability distribution, and the measured muon flux probability distribution at any longitude and latitude represents the probability distribution obeyed by the muon flux detected by the cosmic ray muon detection system at the longitude and latitude; The longitude and latitude determination module is used to determine the target longitude and latitude corresponding to the target location according to the measured muon flux and the position distribution mapping relationship.

9. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to implement the method described in any one of claims 1 to 7 when executing the instructions stored in the memory.

10. A non-volatile computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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