Obstruction environment recognition method, device, computer storage medium and terminal

Abstract

This disclosure discloses a method, apparatus, computer storage medium, and terminal for identifying occlusion environments. In this embodiment, a preset number of axes are set at equal intervals in the sky where satellites are distributed, with the location of the positioning chip as the center and at a predetermined elevation angle. For each satellite, a first weight is calculated for all axes within a preset azimuth threshold range. Satellites are no longer limited to a single interval region. The first weight quantifies the signal reception strength of the positioning chip for different axes within the satellite azimuth threshold range. For each axis, all calculated first weights are accumulated, and the accumulated result is used as the second weight for that axis. This quantifies the signal reception of each axis for all satellites. Based on the second weight, the occlusion environment of the positioning chip is determined. Combining the first and second weights solves the card boundary problem while improving the quality of occlusion environment identification.

Description

Technical Field

[0001] This article relates to satellite positioning technology, and more particularly to a method, device, computer storage medium, and terminal for identifying obstructed environments. Background Technology

[0002] With the increasing adoption of GNSS in wearable devices, the challenges of GNSS positioning in this field are becoming increasingly prominent, including densely packed buildings, proximity to structures, complex multipath scenarios, and relatively low antenna gain. However, the accuracy requirements for GNSS positioning are constantly rising. Therefore, how to continuously improve GNSS positioning performance in wearable devices under harsh environments is a topic worthy of ongoing research.

[0003] Among the many research hotspots in GNSS positioning in the wearable field, accurately determining the occlusion environment of the positioning chip is crucial; for example, whether the environment is unilaterally occluded, bilaterally occluded, or open. After accurately determining the occlusion environment of the positioning chip, targeted satellite selection and weighting can be performed to better improve positioning performance.

[0004] Environmental identification methods in related technologies include dividing the sky and space into several intervals, and then counting the number of satellites in each interval to identify the environment. The biggest problem with this method is that satellites near the interval boundary belong to different intervals, resulting in different final environmental identification results, i.e., the boundary problem. How to improve the quality of environmental identification has become a problem to be solved. Summary of the Invention

[0005] This application provides a method for identifying occlusion environments, including: When identifying the obstruction environment of the positioning chip, for each satellite, the first weight of the axis corresponding to the satellite within the preset azimuth threshold range of the satellite is calculated; wherein, the first weight is used to quantify the signal reception strength of the positioning chip for the satellite, the larger the first weight, the stronger the signal reception strength of the satellite; wherein, the axis is set with the positioning chip position as the center, according to a predetermined elevation angle, and at preset intervals in the sky where the satellites are distributed; For each axis, sum up all the calculated first weights of that axis, and use the summation result as the second weight of that axis. The occlusion environment of the positioning chip is determined based on the second weights of all obtained axes.

[0006] On the other hand, embodiments of this application also provide a computer storage medium storing a computer program, which, when executed by a processor, implements the above-described occlusion environment recognition method.

[0007] Furthermore, embodiments of this application also provide a terminal, including: a memory and a processor, wherein the memory stores a computer program; wherein, The processor is configured to execute computer programs in memory; When the computer program is executed by the processor, it implements the occlusion environment recognition method described above.

[0008] Furthermore, embodiments of this application also provide an occlusion environment recognition device, including: a weight calculation unit, an accumulation unit, and a recognition processing unit; wherein, The weight calculation unit is configured as follows: when identifying the occlusion environment of the positioning chip, for each satellite, calculate the first weight of the axis corresponding to the satellite within the preset azimuth threshold range of the satellite; wherein, the first weight is used to quantify the signal reception strength of the positioning chip for the satellite, and the larger the first weight, the stronger the signal reception strength of the satellite; wherein, the axis is set with the positioning chip position as the center, according to a predetermined elevation angle, and at preset intervals in the sky where the satellites are distributed; The accumulation unit is set as follows: for each axis, all the calculated first weights of that axis are accumulated, and the accumulation result is used as the second weight of that axis. The recognition processing unit is configured to determine the occlusion environment of the positioning chip based on the second weights of all obtained axes.

[0009] In this embodiment, the positioning chip's location is used as the center. A predetermined number of axes are set at equal intervals in the sky where satellites are distributed, according to a predetermined elevation angle. For each satellite, the first weight of all axes within a predetermined azimuth threshold range is calculated. Satellites are no longer limited to a single interval region. The first weight quantifies the signal reception strength of the positioning chip for different axes within the satellite's azimuth threshold range. For each axis, all calculated first weights are accumulated, and the accumulated result is used as the second weight of that axis. This quantifies the signal reception of each axis for all satellites. Based on the second weight, the occlusion environment of the positioning chip is determined. Combining the first and second weights solves the card boundary problem while improving the quality of occlusion environment recognition.

[0010] Other features and advantages of this application will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the application. Other advantages of this application can be realized and obtained by means of the solutions described in the description and the accompanying drawings. Attached Figure Description

[0011] The accompanying drawings are used to provide an understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0012] Figure 1This is a flowchart of the occlusion environment recognition method according to an embodiment of the present disclosure; Figure 2 This is a schematic diagram of the shaft according to an embodiment of the present disclosure; Figure 3 This is a structural block diagram of the occlusion environment recognition device according to an embodiment of the present disclosure. Detailed Implementation

[0013] This application describes several embodiments, but these descriptions are exemplary and not limiting, and it will be apparent to those skilled in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with or in lieu of any other feature or element in any other embodiment.

[0014] This application includes and contemplates combinations of features and elements known to those skilled in the art. The embodiments, features, and elements disclosed in this application can also be combined with any conventional features or elements to form unique inventive solutions. Any feature or element of any embodiment can also be combined with features or elements from other inventive solutions to form another unique inventive solution. Therefore, it should be understood that any feature shown and / or discussed in this application can be implemented individually or in any suitable combination. Therefore, the embodiments are not limited except by the limitations imposed by the appended claims and their equivalents. Furthermore, various modifications and changes can be made within the scope of the appended claims.

[0015] Furthermore, in describing representative embodiments, the specification may have presented methods and / or processes as a specific sequence of steps. However, the method or process should not be limited to the specific order of steps described herein, to the extent that it does not depend on such a specific order. As will be understood by those skilled in the art, other sequences of steps are also possible. Therefore, the specific order of steps set forth in the specification should not be construed as a limitation of the claims. Moreover, the claims concerning the method and / or process should not be limited to the steps performed in the written order, and those skilled in the art will readily understand that these orders can be varied and still remain within the spirit and scope of the embodiments of this application.

[0016] Figure 1 This is a flowchart of the occlusion environment recognition method according to an embodiment of this disclosure, such as... Figure 1 As shown, it includes: Step 101: When identifying the obstruction environment of the positioning chip, for each satellite, calculate the first weight of the axis corresponding to the satellite within the preset azimuth threshold range of the satellite; wherein, the first weight is used to quantify the signal reception strength of the positioning chip for the satellite, the larger the first weight, the stronger the signal reception strength of the satellite; wherein, the axis is set with the positioning chip position as the center, according to a predetermined elevation angle, and at preset intervals of azimuth angle in the sky where the satellites are distributed; Step 102: For each axis, sum up all the calculated first weights of that axis, and use the sum as the second weight of that axis; Step 103: Determine the occlusion environment of the positioning chip based on the second weights of all axes obtained.

[0017] In this embodiment, the positioning chip's location is used as the center. A predetermined number of axes are set at equal intervals in the sky where satellites are distributed, according to a predetermined elevation angle. For each satellite, the first weight of all axes within a predetermined azimuth threshold range is calculated. Satellites are no longer limited to a single interval region. The first weight quantifies the signal reception strength of the positioning chip for different axes within the satellite's azimuth threshold range. For each axis, all calculated first weights are accumulated, and the accumulated result is used as the second weight of that axis. This quantifies the signal reception of each axis for all satellites. Based on the second weight, the occlusion environment of the positioning chip is determined. Combining the first and second weights solves the card boundary problem while improving the quality of occlusion environment recognition.

[0018] Azimuth is the horizontal angle measured from a north-pointing line to a target direction line in a clockwise direction. Simply put, it's an angle value used to precisely represent direction.

[0019] In one exemplary embodiment, the number of axes set according to equally spaced azimuth angles is greater than or equal to 8, including any one of the following: 8 axes, 12 axes, and 24 axes, etc.

[0020] The number of axes in this exemplary embodiment can be adjusted based on the results of occlusion environment identification.

[0021] In one exemplary embodiment, the axes are set with the location of the positioning chip as the center, and 12 axes are set at 30-degree azimuth intervals in the sky where the satellites are distributed, according to the elevation angles of 30 degrees, 45 degrees, or 60 degrees.

[0022] The method for setting the 12 axes described in this exemplary embodiment is as follows: with the position of the positioning chip as the center, the elevation angle is set to 45 degrees, and the azimuth angles at equal intervals are 0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, and 330 degrees. Figure 2 This is a schematic diagram of the shaft according to an embodiment of the present disclosure, as shown below. Figure 2 As shown, the axes are numbered from 1 to 12 according to the azimuth angle from smallest to largest.

[0023] In one exemplary embodiment, the initial second weight of each axis is 0.

[0024] In one exemplary embodiment, for each satellite, calculating the first weight of the axis corresponding to the satellite within a preset azimuth threshold range of that satellite includes: For satellite i and axis k located within the azimuth threshold range of satellite i, calculate the first weight value corresponding to axis k within the azimuth threshold range of satellite i based on the azimuth angle between satellite i and axis k, the elevation angle between satellite i and axis k, and the carrier-to-noise ratio (CN0) weight value of satellite i.

[0025] In one exemplary embodiment, the first weight value corresponding to axis k within the azimuth threshold range of satellite i is Value. i_k Value i_k Calculated using the following formula: Value i_k = cos(azDiff i_k ) * cos(eleDiff i_k ) * CN0Value i ; In the formula, azDiff i_k It is the azimuth angle between satellite i and axis k, eleDiff i_k CN0Value is the angle between the elevation angles of satellite i and axis k. i CN0 is the weight value of satellite i.

[0026] In one exemplary embodiment, the CN0 weight value CN0Value of satellite i i Calculated using the following formula: CN0Valuei = a1*(CN0 – a2)* (CN0 – a2) + a3; In the formula, CN0 is the carrier-to-noise ratio, and a1, a2 and a3 are pre-set fitting parameters.

[0027] This exemplary embodiment can select cosine function fitting, linear fitting, or curve fitting, etc., for parameter fitting, without limiting the specific fitting method.

[0028] In one exemplary embodiment, at epoch t, ​​it is assumed that the azimuth angle of satellite i is az. i The azimuth threshold range of this satellite can be set to (az). i -TH1, az i+TH1), the azimuth angle of satellite i+1 is az i+1 The azimuth threshold range of this satellite can be set to (az). i+1 -TH1, az i+1 +TH1), TH1 can be analyzed and set by technicians. For example, it can be set from 30 degrees to 90 degrees. Assuming TH1 is 45 degrees, axis 1 is included in the azimuth threshold range of satellite i and satellite i+1. Then, after the first weight of axis 1 corresponding to satellite i and satellite i+1 is accumulated, the second weight of axis 1 can be obtained. This exemplary embodiment does not only count the case of one interval in the related technology. It calculates the corresponding first weight for axes located in the preset azimuth threshold range of the satellite. The signal reception strength of the positioning chip for the satellite is quantified by the weight. Thus, the satellite reception situation of the current environment of the positioning chip can be objectively and accurately described. Therefore, the environment can be accurately identified, and the boundary problem of environment identification is solved.

[0029] This exemplary embodiment calculates the corresponding first weight based on the satellite distribution at different epochs, and then uses the calculated second weight to determine the occlusion environment of the positioning chip at different epochs.

[0030] In one exemplary embodiment, for each axis, all the calculated first weights of that axis are summed, including summing using the following formula: Value k = ; In the formula, Step 101: Calculate the first weight of axis k within the azimuth threshold range of satellite j, where M is the set of all satellites containing axis k within the azimuth threshold range.

[0031] In one exemplary embodiment, after traversing all satellites in step 101, a second weight for each axis can be obtained based on step 102.

[0032] In one exemplary embodiment, determining the occlusion environment of the positioning chip based on the obtained second weights of all axes includes: Normalize the second weights of all axes; The occlusion environment of the positioning chip is determined based on the values ​​of the second weight before and after normalization. The occlusion environment of the positioning chip includes one or any combination of the following: open, single occlusion, double occlusion, triple occlusion, and severe occlusion.

[0033] In one exemplary embodiment, single occlusion can mean that half of the environment in which the positioning chip is located is occluded, double occlusion can mean that both sides of the environment in which the positioning chip is located are occluded except for the middle area, and triple occlusion can mean that three-quarters of the environment in which the positioning chip is located is occluded.

[0034] In one exemplary embodiment, determining the occlusion environment of the positioning chip based on the values ​​of the second weight before and after normalization processing includes: When the minimum value of the second weight before normalization is greater than the preset first threshold, and the minimum value of the second weight after normalization is greater than the preset second threshold, the occlusion environment of the positioning chip is determined to be an open environment. When half of the normalized second weights are greater than the third threshold, and the other half are less than the fourth threshold, and the axes corresponding to the normalized second weights greater than the third threshold are continuously distributed, the occlusion environment of the positioning chip is determined to be single occlusion. Using the location of the positioning chip as the center, draw a circle on the ground plane. Project the set axis onto the drawn circle according to the set axis orientation angle. The occlusion environment of the positioning chip is determined through the following process: When the points on the circle where the normalized second weight is greater than the fifth threshold form a rectangle, and both sides of the rectangle have axes where the normalized second weight is less than the sixth threshold, and the maximum value of the unnormalized second weight is greater than the seventh threshold, and the minimum value of the unnormalized second weight is less than the eighth threshold, the occlusion environment of the positioning chip is determined to be double occlusion. When the points on the circle where the normalized second weight is greater than the ninth threshold form a right-angled sector, and the normalized second weights of all axes other than the right-angled sector are less than the tenth threshold, and the maximum value of the second weight before normalization is greater than the eleventh threshold, and the minimum value of the second weight before normalization is less than the twelfth threshold, then the occlusion environment of the positioning chip is determined to be triple occlusion. If the maximum value of the second weight before normalization is less than the preset thirteenth threshold, the occlusion environment of the positioning chip is determined to be severely occluded.

[0035] This exemplary embodiment takes 12 axes as an example. The second weights of the 12 axes are Value_1-Value_12. After normalization, we get Value_norm1-Value_norm12. The maximum value Value_max and the minimum value Value_min of the second weights of the 12 axes before normalization are obtained, and the maximum value Value_norm_max and the minimum value Value_norm_min of the second weights after normalization are obtained. It is determined to be open when the following conditions are met: Value_norm_min > T1 and Value_min > T2; where T1 is the first threshold and T2 is the second threshold; It is determined to be single - shaded when the following conditions are met: The Value_norm of all axes in one - half of the sky is greater than T3, while the Value_norm of all axes in the opposite half of the sky is less than T4; for example, the second weights of axes 1, 2, 3, 4, 5, and 6 are very large and all greater than T3, while the second weights of axes 7, 8, 9, 10, 11, and 12 are very small and all less than T4. T3 is the third threshold and T4 is the fourth threshold; It is determined to be double - shaded when the following conditions are met: Value_norm is very large in a rectangle and very small on both sides, and Value_max > T5, Value_min < TH6; for example, the second weights of axes 1, 2, 3, 7, 8, and 9 before and after normalization are very large, while the second weights of axes 4, 5, 6, 10, 11, and 12 before and after normalization are very small, and Value_max > T5, Value_min < T6; T5 is the seventh threshold and T6 is the eighth threshold; It is determined to be triple - shaded when the following conditions are met: Value is very large in a right - angled area and very small in other areas, and Value_max > T7, Value_min < T8; for example, the second weights of axes 1, 2, 3, and 4 before normalization are very large, and the second weights of axes 5, 6, 7, 8, 9, 10, 11, and 12 before and after normalization are very small, and Value_max > T7, Value_min < T8. T7 is the eleventh threshold and T8 is the twelfth threshold; It is determined to be severely occluded when the following conditions are met: The second weights of all axes before normalization are very small, and Value_max < T11, where T11 is the thirteenth threshold.

[0036] The processing of determining the above - mentioned occlusion environment in this exemplary embodiment can be implemented by machine learning or logical recognition methods, and this exemplary embodiment does not limit this. Through the above processing, the problem of getting stuck at the boundary is effectively solved, and the quality of occlusion environment recognition is improved.

[0037] This embodiment of the present disclosure also provides a computer storage medium. A computer program is stored in the computer storage medium, and when the computer program is executed by a processor, the above - mentioned occlusion environment recognition method is implemented.

[0038] This embodiment of the present disclosure also provides a terminal, including: a memory and a processor, and a computer program is stored in the memory; where The processor is configured to execute the computer program in the memory; When the computer program is executed by the processor, the occlusion environment recognition method as described above is implemented.

[0039] Figure 3 This is a structural block diagram of the occlusion environment recognition device according to an embodiment of the present disclosure, as shown below. Figure 3 As shown, it includes: a weight calculation unit, an accumulation unit, and a recognition processing unit; wherein, The weight calculation unit is configured as follows: when identifying the occlusion environment of the positioning chip, for each satellite, calculate the first weight of the axis corresponding to the satellite within the preset azimuth threshold range of the satellite; wherein, the first weight is used to quantify the signal reception strength of the positioning chip for the satellite, and the larger the first weight, the stronger the signal reception strength of the satellite; wherein, the axis is set with the positioning chip position as the center, according to a predetermined elevation angle, and at preset intervals in the sky where the satellites are distributed; The accumulation unit is set as follows: for each axis, all the calculated first weights of that axis are accumulated, and the accumulation result is used as the second weight of that axis. The recognition processing unit is configured to determine the occlusion environment of the positioning chip based on the second weights of all obtained axes.

[0040] In one exemplary embodiment, the number of axes set according to equally spaced azimuth angles is greater than or equal to eight, and includes any one of the following: 8 axes, 12 axes, and 24 axes.

[0041] In one exemplary embodiment, the axes are set with the location of the positioning chip as the center, and 12 axes are set at 30-degree azimuth intervals in the sky where the satellites are distributed, according to the elevation angles of 30 degrees, 45 degrees, or 60 degrees.

[0042] In one exemplary embodiment, the weight calculation unit is configured as follows: For satellite i and axis k located within the azimuth threshold range of satellite i, calculate the first weight value corresponding to axis k within the azimuth threshold range of satellite i based on the azimuth angle between satellite i and axis k, the elevation angle between satellite i and axis k, and the carrier-to-noise ratio (CN0) weight value of satellite i.

[0043] In one exemplary embodiment, the first weight value corresponding to axis k within the azimuth threshold range of satellite i is Value. i_k Value i_k Calculated using the following formula: Value i_k = cos(azDiff i_k ) * cos(eleDiff i_k ) * CN0Value i ; In the formula, azDiff i_k It is the azimuth angle between satellite i and axis k, eleDiff i_kCN0Value is the angle between the elevation angles of satellite i and axis k. i CN0 is the weight value of satellite i.

[0044] In one exemplary embodiment, the CN0 weight value CN0Value of satellite i i Calculated using the following formula: CN0Valuei = a1*(CN0 – a2)* (CN0 – a2) + a3; In the formula, CN0 is the carrier-to-noise ratio, and a1, a2 and a3 are pre-set fitting parameters.

[0045] In one exemplary embodiment, the identification processing unit is configured as follows: Normalize the second weights of all axes; The occlusion environment of the positioning chip is determined based on the values ​​of the second weight before and after normalization. The occlusion environment of the positioning chip includes one or any combination of the following: open, single occlusion, double occlusion, triple occlusion, and severe occlusion.

[0046] In one exemplary embodiment, single occlusion can mean that half of the environment in which the positioning chip is located is occluded, double occlusion can mean that both sides of the environment in which the positioning chip is located are occluded except for the middle area, and triple occlusion can mean that three-quarters of the environment in which the positioning chip is located is occluded.

[0047] In one exemplary embodiment, the identification processing unit is configured to determine the occlusion environment of the positioning chip based on the values ​​of the second weight before normalization processing and the second weight after normalization processing, including: When the minimum value of the second weight before normalization is greater than the preset first threshold, and the minimum value of the second weight after normalization is greater than the preset second threshold, the occlusion environment of the positioning chip is determined to be an open environment. When half of the normalized second weights are greater than the third threshold, and the other half are less than the fourth threshold, and the axes corresponding to the normalized second weights greater than the third threshold are continuously distributed, the occlusion environment of the positioning chip is determined to be single occlusion. Using the location of the positioning chip as the center, draw a circle on the ground plane. Project the set axis onto the drawn circle according to the set axis orientation angle. The occlusion environment of the positioning chip is determined through the following process: When the points on the circle where the normalized second weight is greater than the fifth threshold form a rectangle, and both sides of the rectangle have axes where the normalized second weight is less than the sixth threshold, and the maximum value of the unnormalized second weight is greater than the seventh threshold, and the minimum value of the unnormalized second weight is less than the eighth threshold, the occlusion environment of the positioning chip is determined to be double occlusion. When the points on the circle where the normalized second weight is greater than the ninth threshold form a right-angled sector, and the normalized second weights of all axes other than the right-angled sector are less than the tenth threshold, and the maximum value of the second weight before normalization is greater than the eleventh threshold, and the minimum value of the second weight before normalization is less than the twelfth threshold, then the occlusion environment of the positioning chip is determined to be triple occlusion. If the maximum value of the second weight before normalization is less than the preset thirteenth threshold, the occlusion environment of the positioning chip is determined to be severely occluded.

[0048] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term "computer storage medium" includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

Claims

1. A method for recognizing occlusion environments, characterized in that, include: When identifying the obstruction environment of the positioning chip, for each satellite, the first weight of the axis located within the preset azimuth threshold range of the satellite is calculated. The first weight is used to quantify the signal reception strength of the satellite on the axis. The larger the first weight, the stronger the signal reception strength of the satellite. The axis is set with the positioning chip position as the center and the azimuth angles at preset intervals in the sky where the satellites are distributed, according to a predetermined elevation angle. For each axis, sum up all the calculated first weights of that axis, and use the summation result as the second weight of that axis. The occlusion environment of the positioning chip is determined based on the second weights of all obtained axes.

2. The occlusion environment recognition method according to claim 1, characterized in that, The elevation angle is 30 degrees, 45 degrees, or 60 degrees, and the number of axes set according to the preset interval of azimuth angles is any one of the following: 8-axis, 12-axis and 24-axis.

3. The occlusion environment recognition method according to claim 1, characterized in that, The step of calculating the first weight of each satellite for the axis located within the preset azimuth threshold range of that satellite includes: For satellite i and axis k located within the azimuth threshold range of satellite i, the first weight value corresponding to axis k within the azimuth threshold range of satellite i is calculated based on the azimuth angle between satellite i and axis k, the elevation angle between satellite i and axis k, and the carrier-to-noise ratio CN0 weight value of satellite i.

4. The occlusion environment recognition method according to claim 3, characterized in that, The first weight value corresponding to axis k within the azimuth threshold range of satellite i is Value. i_k Value i_k Calculated using the following formula: Value i_k = cos(azDiff i_k ) * cos(eleDiff i_k ) * CN0Value i ; In the formula, azDiff i_k It is the azimuth angle between the satellite i and the axis k, eleDiff i_k CN0Value is the angle between the elevation angle of the satellite i and the axis k. i Let CN0 be the weight value of satellite i.

5. The occlusion environment recognition method according to claim 1, characterized in that, The CN0 weight value of satellite i is CN0Value. i CN0Value i Calculated using the following formula: CN0Valuei = a1*(CN0 – a2)* (CN0 – a2) + a3; In the formula, CN0 is the carrier-to-noise ratio, and a1, a2 and a3 are pre-set fitting parameters.

6. The occlusion environment recognition method according to any one of claims 1 to 5, characterized in that, The step of determining the occlusion environment of the positioning chip based on the obtained second weights of all axes includes: The second weights of all axes are normalized. The occlusion environment of the positioning chip is determined based on the values ​​of the second weight before normalization and the second weight after normalization. The occlusion environment of the positioning chip includes one or any combination of the following: open, single occlusion, double occlusion, triple occlusion, and severe occlusion. Single occlusion means that half of the environment in which the positioning chip is located is occluded. Double occlusion means that both sides of the environment in which the positioning chip is located are occluded except for the middle area. Triple occlusion means that three-quarters of the environment in which the positioning chip is located is occluded.

7. The occlusion environment recognition method according to claim 6, characterized in that, The step of determining the occlusion environment of the positioning chip based on the values ​​of the second weight before normalization and the second weight after normalization includes: When the minimum value of the second weight before normalization is greater than the preset first threshold, and the minimum value of the second weight after normalization is greater than the preset second threshold, the occlusion environment of the positioning chip is determined to be an open environment. If half of the normalized second weights are greater than a preset third threshold, and the other half of the normalized second weights are less than a preset fourth threshold, and the axes corresponding to the normalized second weights greater than the third threshold are continuously distributed, then the occlusion environment of the positioning chip is determined to be single occlusion. Using the location of the positioning chip as the center, draw a circle on the ground plane. Project the set axis onto the drawn circle according to the set axis orientation angle. The occlusion environment of the positioning chip is determined through the following process: The points on the circle where the normalized second weight is greater than the preset fifth threshold form a rectangle. On both sides of this rectangle, there are axes where the normalized second weight is less than the sixth threshold. Furthermore, the maximum value of the unnormalized second weight is greater than the preset seventh threshold, and the minimum value of the unnormalized second weight is less than the preset eighth threshold. In this case, the occlusion environment of the positioning chip is determined to be double occlusion. The points on the circle where the normalized second weight is greater than the preset ninth threshold form a right-angled sector. The normalized second weights of all axes other than the right-angled sector are less than the preset tenth threshold. Furthermore, the maximum value of the second weight before normalization is greater than the preset eleventh threshold, and the minimum value of the second weight before normalization is less than the preset twelfth threshold. Therefore, the occlusion environment of the positioning chip is determined to be triple-occlusion. When the maximum value of the second weight before normalization is less than the preset thirteenth threshold, the occlusion environment of the positioning chip is determined to be severely occluded.

8. A computer storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the occlusion environment recognition method as described in any one of claims 1 to 7.

9. A terminal, characterized in that, include: A memory and a processor, wherein the memory stores a computer program; wherein, The processor is configured to execute computer programs in memory; When the computer program is executed by the processor, it implements the occlusion environment recognition method as described in any one of claims 1 to 7.

10. An occlusion environment recognition device, characterized in that, include: The system comprises a weight calculation unit, an accumulation unit, and an identification processing unit; among which, The weight calculation unit is configured as follows: when identifying the occlusion environment of the positioning chip, for each satellite, calculate the first weight of the axis corresponding to the satellite within the preset azimuth threshold range of the satellite; wherein, the first weight is used to quantify the signal reception strength of the positioning chip for the satellite, and the larger the first weight, the stronger the signal reception strength of the satellite; wherein, the axis is set with the positioning chip position as the center, according to a predetermined elevation angle, and at preset intervals in the sky where the satellites are distributed; The accumulation unit is set as follows: for each axis, all the calculated first weights of that axis are accumulated, and the accumulation result is used as the second weight of that axis. The recognition processing unit is configured to determine the occlusion environment of the positioning chip based on the second weights of all obtained axes.

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