WO2023198072A1

WO2023198072A1 - Electronic device and positioning method therefor, and medium

Info

Publication number: WO2023198072A1
Application number: PCT/CN2023/087670
Authority: WO
Inventors: 黄庆超; 吴泰洋; 鲁鸿宇; 丁根明
Original assignee: 华为技术有限公司
Priority date: 2022-04-14
Filing date: 2023-04-11
Publication date: 2023-10-19
Also published as: CN116953735A

Abstract

The present application relates to the technical fields of signal processing and interference prevention; and particularly relates to an electronic device and a positioning method therefor, and a medium. The positioning method comprises: in response to an electronic device starting a positioning service, acquiring a signal power change sequence of a plurality of satellite signals within a preset time period; on the basis of the signal power change sequence of the plurality of satellite signals, determining whether a fading feature between the plurality of satellite signals within the preset time period meets a positioning requirement; corresponding to fading features between the plurality of satellite signals within a plurality of preset time periods meeting the positioning requirement, acquiring a positioning result, which is generated on the basis of the plurality of satellite signals; and if the positioning requirement is not met, disabling a satellite positioning service and calling another positioning service, and giving an alarm prompt. By means of the positioning method provided in the present application, an electronic device can identify a spoofing attack of a satellite signal according to significantly different fading features that are present between satellite signals, which are acquired by means of different propagation channels corresponding to different navigation satellites, thereby solving the security problem in satellite navigation technology.

Description

Electronic equipment and positioning methods and media thereof

This application claims priority to the Chinese patent application filed with the China Patent Office on April 14, 2022, with the application number 202210394155.2 and the application name "Electronic Equipment and Positioning Methods and Media Therefor", the entire content of which is incorporated into this application by reference. middle.

Technical field

The present application relates to the technical fields of signal processing and anti-interference, and in particular to an electronic device and its positioning method and medium.

Background technique

Global Navigation Satellite Systems (GNSS) generally refers to all satellite navigation systems, including: the United States’ Global Positioning System (GPS), Russia’s Global Navigation Satellite System (Glonass), Europe's Galileo satellite navigation system (Galileo satellite navigation system, Galileo), China's Beidou satellite navigation system, etc. GNSS can provide positioning, velocity and time services (Position, Velocity and Time, PVT) and is widely used in vehicle or personal navigation, aircraft navigation and landing systems, power transmission networks, digital communication networks, precision agriculture, geological exploration and other fields.

Since the satellite signals reaching the ground are very weak, and the certification information and signal formats of civilian satellite navigation systems are public and easy to obtain, malicious location spoofing has gradually become an important threat to satellite navigation systems. For example, the spoofing device can block the electronic device from obtaining the real satellite signal from the satellite navigation system by forwarding a processed or autonomously generated spoofing signal that is similar to the real satellite signal, causing the electronic device to accept the spoofing signal, causing the electronic device to act according to the spoofing signal. Getting wrong PVT results. The spoofing signal here may be a signal generated by a spoofing device that has the same authentication information and signal format as the real satellite signal but carries different PVT data. Therefore, a spoofing signal detection technology is needed to ensure that electronic devices can eliminate spoofing signals and receive real satellite signals from satellite navigation systems.

Contents of the invention

Embodiments of the present application provide an electronic device and its positioning method and medium.

The first aspect of this application provides a positioning method applied to electronic equipment, characterized in that the method includes:

In response to the electronic device initiating the positioning service, obtain a signal power change sequence of multiple satellite signals within a preset time period;

Based on the signal power change sequence of multiple satellite signals, determine whether the fading characteristics between the signals of multiple satellite signals within the preset time period meet the positioning requirements;

Corresponding to the fading characteristics of multiple satellite signals in multiple preset time periods, the positioning requirements are met, and the positioning results generated based on the multiple satellite signals are obtained.

That is, in the embodiment of the present application, the electronic device here may be a terminal device with positioning function such as a mobile phone or a tablet computer. The positioning service here can be a navigation application that implements positioning through GPS. The preset time period here can be the time period during which the electronic device continues to obtain satellite signals after turning on the positioning service. The positioning result here can be the time period corresponding to the positioning service. bit results, for example, the navigation route corresponding to the navigation service. Electronic equipment can collect time-varying satellite signals within a preset time period and calculate the correlation coefficient of the power sequence of each satellite signal. The correlation coefficient here can be used to represent the similarity between the fading characteristics corresponding to each satellite signal. , compare the correlation coefficient with the preset threshold. If the correlation coefficient between the fading characteristics corresponding to each satellite signal is less than the preset threshold, it means that the correlation coefficient is small, indicating that the correlation between the fading characteristics corresponding to each satellite signal is If the similarity is low, the satellite signal can be determined to be a real signal; if the correlation coefficient between the fading characteristics corresponding to each satellite signal is greater than the preset threshold, it means that the correlation coefficient is large, indicating that the fading characteristics corresponding to each group of satellite signals are The similarity between them is high, and each satellite signal can be determined to be a spoofing signal.

Through the positioning method provided by this application, electronic devices can identify satellite signal spoofing attacks based on the significantly different fading characteristics of satellite signals acquired by different navigation satellites corresponding to different propagation channels in the satellite navigation system, effectively solving the problems in satellite navigation technology. Security issues to create a secure foundation for location-based services.

In a possible implementation of the first aspect above, obtaining the signal power change sequence of multiple satellite signals within a preset time period includes:

Identify the navigation satellite numbers corresponding to multiple satellite signals used by positioning services within a preset time period;

A sequence of signal power changes of the signal is obtained based on tracking the signal power of multiple satellite signals within a preset time period using navigation satellite numbers.

In a possible implementation of the first aspect above, positioning requirements include:

The average value of the correlation coefficient between the fading characteristics of the signal power of each satellite signal within the preset time period is lower than the preset threshold, where the correlation coefficient is used to represent two satellite signals in the signal power change sequence of multiple satellite signals. The similarity of fading characteristics between signal power change sequences.

In a possible implementation of the above first aspect, the preset threshold is related to a motion state of the electronic device, where the motion state is used to indicate that the electronic device is in at least one of a stationary state or a moving state.

That is, in the embodiment of the present application, the positioning service of the electronic device can obtain at least four different satellite signals, and the satellite signals can come from at least four different navigation satellites. The preset threshold here may be related to whether the electronic device is in a stationary state or a moving state, and different preset thresholds are set for the stationary state and the moving state. The electronic device can compare the acquired satellite signal power correlation coefficient with different preset thresholds based on the current status of the electronic device to more accurately determine whether the satellite signal is a real signal or a spoofed signal.

In a possible implementation of the above first aspect, the correlation coefficient is obtained through at least one of Pearson correlation coefficient, Spearman correlation coefficient, Kendall correlation coefficient and similarity measure neural network model.

That is, in the embodiment of the present application, the electronic device can use correlation to measure the fading characteristics of the change sequence corresponding to the signal power of the satellite signal (that is, the signal power change sequence). The specific correlation measurement method includes: through correlation Coefficients and similarity measure neural networks.

In a possible implementation of the first aspect above, the motion state of the electronic device is determined in the following manner:

Determine the speed of the electronic device through its gyroscope sensor and acceleration sensor;

According to the comparison result of the speed of the electronic device and the speed threshold, the motion state of the electronic device is determined.

In a possible implementation of the first aspect above, it also includes:

The fading characteristics corresponding to multiple satellite signals within multiple preset time periods do not meet the positioning requirements, prompting the user that the positioning service is abnormal.

In a possible implementation of the above first aspect, the method for prompting the user to locate the service abnormality includes at least one of the following: A sort of:

Electronic devices prompt to turn off location services;

The electronic device prompts that the satellite signal received by the positioning service is incorrect;

The electronic device prompts that location services will be re-enabled.

The second aspect of the present application provides an electronic device, which is characterized in that it includes:

A processor, configured to execute the positioning method provided in the first aspect; and

Memory, which may be coupled or decoupled from the processor, stores instructions for execution by the processor.

A third aspect of the present application provides a computer-readable storage medium, which is characterized in that the computer-readable storage medium contains instructions, and when the instructions are executed by the processor of the electronic device, the electronic device enables the electronic device to implement the aforementioned method provided in the first aspect. Positioning method.

A fourth aspect of the present application provides a computer program product, which is characterized in that it includes: a computer-readable storage medium, and the computer-readable storage medium contains computer program code for executing the positioning method provided in the first aspect.

Description of the drawings

Figure 1 shows a schematic diagram of a scenario in which an electronic device receives a satellite signal (GNSS signal) according to an embodiment of the present application;

Figure 2 shows a schematic diagram of a fading curve of an electronic device receiving a satellite signal (GNSS signal) according to an embodiment of the present application;

Figure 3 shows a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present application;

Figure 4 shows a schematic flow chart of a positioning method according to an embodiment of the present application;

Figure 5 shows a schematic diagram of a positioning method according to an embodiment of the present application;

Figure 6 shows a schematic flow chart of a positioning method according to an embodiment of the present application;

Figure 7 shows a schematic flow chart of a positioning method according to an embodiment of the present application;

Figure 8 shows a schematic flowchart of a positioning method according to an embodiment of the present application.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application clearer, the embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

FIG. 1 shows a schematic diagram of a scenario in which an electronic device 100 receives a GNSS signal (that is, a satellite signal) from a satellite navigation system 200 and receives a spoofing signal from a spoofing device 300 according to some embodiments of the present application. The spoofing device 300 here may be an electronic device that generates a spoofing signal similar to the GNSS signal of the satellite navigation system 200 . As shown in FIG. 1 , the electronic device 100 is running a PVT service (eg, positioning service), and the PVT service receives real GNSS signals from the satellite navigation system 200 . At this time, the spoofing device 300 can generate a spoofing signal that has the same authentication information, signal format, etc. as the real GNSS signal sent by the satellite navigation system 200 but has a larger signal power and carries different PVT data to implement PVT services for the electronic device 100 Control and complete the spoofing attack on the electronic device 100. The specific process of the spoofing device 300 implementing spoofing interference includes: after receiving the real GNSS signal, the spoofing device 300 then sends a high-power spoofing signal with a frequency similar to the real GNSS signal, so that the electronic device 100 that is tracking and processing the real GNSS signal The tracking loop loses lock, that is, the electronic device 100 is in a state of not receiving the GNSS signal of the satellite navigation system 200, and then When the electronic device 100 enters the loss-of-lock and reacquisition phase, since the spoofing signal is similar to the real GNSS signal and the power of the spoofing signal is higher than the real GNSS signal, the electronic device 100 may misjudge the high-power spoofing signal as the real one. The GNSS signal enables the electronic device 100 to obtain and continue to receive the spoofed signal.

Continuing to refer to Figure 1, it can be seen that when the electronic device 100 receives real GNSS signals from the satellite navigation system 200 and uses PVT services, the GNSS signals will be affected by the atmosphere during propagation, causing the electromagnetic wave amplitude of the GNSS signals to change over time. Rapid irregular changes occur, that is, the rapid fading of electromagnetic waves. The electromagnetic wave amplitude of the GNSS signal here can be represented by the Carrier Noise Ratio (CNR) of the GNSS signal power. For example: in the ionosphere above the earth between 50 and 100 kilometers (kilometer, km) from the ground, gas molecules are ionized by various rays, forming a large amount of plasma. The ionosphere can produce ionospheric scintillation on GNSS signals, causing The electromagnetic wave amplitude of the GNSS signal undergoes short-period irregular changes. At the same time, the GNSS signal will also be affected by ambient temperature, air temperature, air pressure, etc. during the propagation process, causing the GNSS signal to refract and rapid fading of the electromagnetic wave amplitude. Since the propagation paths of real GNSS signals are from different navigation satellites to electronic equipment, they are affected by different atmospheric effects during the propagation process. Therefore, different GNSS signal powers (carrier-to-noise ratios) have different fading characteristics; as for GNSS spoofing signals, The propagation path of the GNSS spoofing signal is from the spoofing device to the electronic device. The GNSS spoofing signal will not be affected by the atmosphere, and the signal propagation path is the same. Therefore, the fading characteristics of each GNSS spoofing signal sent by the spoofing device 300 are similar.

In order to solve the problem that the electronic device receives the GNSS spoofing signal sent by the spoofing device, causing the electronic device to generate erroneous PVT results, embodiments of the present application provide a positioning method. The electronic device can calculate the fading characteristics of each received GNSS signal by verifying the fading characteristics. The similarity of the fading characteristics between various GNSS signals determines whether the GNSS signal received by the electronic device is a real GNSS signal or a GNSS spoofing signal, and then identifies GNSS spoofing attack behavior.

Specifically, in the positioning method provided by the embodiment of the present application, when the electronic device 100 uses the PVT service by receiving GNSS signals; the electronic device 100 first identifies the navigation satellite number carried by the GNSS signal used in the current PVT solution, that is, The number of Pseudo Random Noise (PRN) is the navigation satellite PRN code. It can be understood that the navigation satellite PRN code here is public. The spoofing device can generate and send a spoofing signal similar to the real GNSS signal based on the desired PVT spoofing result and combined with the corresponding ephemeris data (the location of the navigation satellite).

The electronic device 100 obtains the number (PRN code) of the satellite currently used in the PVT service, tracks the power change of the GNSS signal (satellite signal) within a preset time period according to the PRN code, and then obtains the signal power corresponding to the GNSS signal (i.e., carrier-to-noise ratio). ) data sequence (the signal power data sequence here can also be called the signal power change sequence). Taking the electronic device 100 using positioning services as an example, the electronic device 100 needs to obtain at least four different GNSS signals. If the GNSS signals are real signals, the at least four different GNSS signals can come from at least four different navigation satellites. If If the GNSS signal is a spoofing signal, then at least four different GNSS signals can be spoofing signals from the same or multiple spoofing devices; the electronic device 100 can track each GNSS signal through the navigation satellite number (PRN code) to obtain at least four sets of GNSS Data sequence of signal power. That is, the electronic device 100 can collect data sequences of at least four groups of GNSS signal powers that change with time within a preset time period, and calculate the correlation coefficient between the power of each group of GNSS signals. The correlation coefficient here can be used to Indicates the similarity between the fading characteristics corresponding to each group of GNSS signals. Compare the correlation coefficient with the preset threshold. If the correlation coefficient between the fading characteristics corresponding to each group of GNSS signals is less than the preset threshold, it indicates correlation. A small coefficient indicates that the similarity between the fading characteristics corresponding to each GNSS signal is low, and the GNSS signal can be determined to be a real signal; if the correlation coefficient between the fading characteristics corresponding to each group of GNSS signals is greater than the preset threshold, it means The larger the correlation coefficient, the higher the similarity between the fading characteristics corresponding to each group of GNSS signals, and the GNSS can be determined. The signal is a deceptive signal.

In the embodiment of the present application, in order to achieve more accurate detection, during the period when the electronic device 100 collects GNSS signals, the electronic device 100 can also collect the inertial navigation data of the electronic device 100, that is, the speed and acceleration data of the electronic device 100, and identify During the collection of GNSS signals by the electronic device 100, whether the electronic device 100 is in a stationary state or a moving state, and different preset thresholds are set for the stationary state and the moving state, so that the electronic device 100 can obtain the GNSS signals according to the current state of the electronic device 100. The power correlation coefficient is compared with different preset thresholds to more accurately determine whether the GNSS signal is a real signal or a spoofed signal. Through the positioning method of the embodiment of the present application, the electronic device 100 can identify GNSS signal spoofing attacks based on the significant differences in the GNSS signals obtained by different navigation satellites corresponding to different propagation channels in the satellite navigation system 200 , effectively solving the problem of satellite navigation technology. security issues, and create a security foundation for location-based services (Location Based Service, LBS).

FIG. 2 shows the fading curve of a data sequence of GNSS signal power (carrier-to-noise ratio) that changes with time for real GNSS signals and GNSS spoofing signals (pseudo signals) collected by an electronic device 100 according to some embodiments of the present application. Schematic diagram. The data sequence in Figure 2 includes: when the electronic device 100 is in a stationary scene and a walking scene (moving scene), the electronic device 100 collects the data sequence of the real GNSS signal and the GNSS spoofing signal as the GNSS signal power changes over time. . It can be seen from the changing trend of each group of GNSS signal data sequences in Figure 2: for false signals (GNSS spoofing signals), the data series of each GNSS signal power (carrier-to-noise ratio) have a highly consistent trend over time; for For real signals (real GNSS signals), the trend consistency of the data sequence of each GNSS signal power (carrier-to-noise ratio) over time is low. In addition, since the stationary scene lacks the component of the change in GNSS signal power (carrier-to-noise ratio) caused by the distance change caused by movement, the stationary scene is less consistent than the moving scene, that is, the GNSS signal power (carrier-to-noise ratio) is similar. Sex will be slightly worse.

It can be understood that the electronic device in the embodiment of the present application may be a terminal device capable of running a navigation application to implement PVT services. For example, the terminal device may include: a vehicle-mounted device, a mobile phone, a tablet computer, a notebook computer, a handheld computer, and a mobile Internet Devices (mobile internet device, MID), wearable devices (for example: smart watches, smart bracelets, pedometers, etc.), personal digital assistants, portable media players, navigation devices, video game devices, set-top boxes, virtual reality and /or augmented reality devices, Internet of Things devices, industrial control devices, streaming media client devices, e-book reading devices, and other devices.

Figure 3 shows a schematic structural diagram of an electronic device 100 according to an embodiment of the present application. The electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, and a universal serial bus (universal serial bus, USB) interface 130. , charging management module 140, power management module 141, battery 142, antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, audio module 170, speaker 170A, receiver 170B, microphone 170C, headphone interface 170D, sensor module 180 , button 190, motor 191, indicator 192, camera 193, display screen 194, and subscriber identification module (subscriber identification module, SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyro sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, and ambient light. Sensor 180L, bone conduction sensor 180M, etc.

It can be understood that the structure illustrated in the embodiment of the present invention does not constitute a specific limitation on the electronic device 100 . In other embodiments of the present application, the electronic device 100 may include more or fewer components than shown in the figures, or some components may be combined, some components may be separated, or some components may be arranged differently. The components illustrated may be presented as hardware, software, or a combination of software and hardware. realized together.

The processor 110 may include one or more processing units. For example, the processor 110 may include an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (image signal). processor, ISP), controller, video codec, digital signal processor (digital signal processor, DSP), baseband processor (BP), and/or neural network processor (neural-network processing unit, NPU), etc. Among them, different processing units can be independent devices or integrated in one or more processors.

In the embodiment of the present application, the electronic device 100 can determine the data sequence of the GNSS signal power (carrier-to-noise ratio) corresponding to each GNSS signal received by the electronic device 100 through the processor 110, and calculate the GNSS signal power ( The correlation coefficient between the carrier-to-noise ratio) determines whether the GNSS signal is a real signal or a spoofed signal.

The processor 110 may also be provided with a memory for storing instructions and data. In some embodiments, the memory in processor 110 is cache memory. This memory may hold instructions or data that have been recently used or recycled by processor 110 . If the processor 110 needs to use the instructions or data again, it can be called directly from the memory. Repeated access is avoided and the waiting time of the processor 110 is reduced, thus improving the efficiency of the system.

The charging management module 140 is used to receive charging input from the charger. Among them, the charger can be a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 140 may receive charging input from the wired charger through the USB interface 130 .

The power management module 141 is used to connect the battery 142, the charging management module 140 and the processor 110. The power management module 141 receives input from the battery 142 and/or the charging management module 140, and supplies power to the processor 110, the internal memory 121, the display screen 194, the camera 193, the wireless communication module 160, and the like. The power management module 141 can also be used to monitor battery capacity, battery cycle times, battery health status (leakage, impedance) and other parameters.

The wireless communication function of the electronic device 100 can be implemented through the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modem processor and the baseband processor.

Antenna 1 and Antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in electronic device 100 may be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve antenna utilization. For example: Antenna 1 can be reused as a diversity antenna for a wireless LAN. In other embodiments, antennas may be used in conjunction with tuning switches.

The mobile communication module 150 can provide solutions for wireless communication including 2G/3G/4G/5G applied on the electronic device 100 .

The wireless communication module 160 can provide applications on the electronic device 100 including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) network), Bluetooth (bluetooth, BT), and global navigation satellites. System (global navigation satellite system, 6NSS), frequency modulation (frequency modulation, FM), near field communication technology (near field communication, NFC), infrared technology (infrared, IR) and other wireless communication solutions.

The electronic device 100 implements display functions through a GPU, a display screen 194, an application processor, and the like. The GPU is an image processing microprocessor and is connected to the display screen 194 and the application processor. GPUs are used to perform mathematical and geometric calculations for graphics rendering. Processor 110 may include one or more GPUs that execute program instructions to generate or alter display information.

The display screen 194 is used to display images, videos, etc. Display 194 includes a display panel. In some embodiments, the electronic device 100 may include 1 or N display screens 194, where N is a positive integer greater than 1.

The electronic device 100 can implement the shooting function through an ISP, a camera 193, a video codec, a GPU, a display screen 194, an application processor, and the like.

Camera 193 is used to capture still images or video. In some embodiments, the electronic device 100 may include 1 or N cameras 193, where N is a positive integer greater than 1.

The external memory interface 120 can be used to connect an external memory card, such as a MicroSD card, to expand the storage capacity of the electronic device 100 . The external memory card communicates with the processor 110 through the external memory interface 120 to implement the data storage function.

Internal memory 121 may be used to store computer executable program code, which includes instructions. The internal memory 121 may include a program storage area and a data storage area. The processor 110 executes various functional applications and data processing of the electronic device 100 by executing instructions stored in the internal memory 121 and/or instructions stored in a memory provided in the processor.

The electronic device 100 can implement audio functions through the audio module 170, the speaker 170A, the receiver 170B, the microphone 170C, the headphone interface 170D, and the application processor. Such as music playback, recording, etc.

The audio module 170 is used to convert digital audio information into analog audio signal output, and is also used to convert analog audio input into digital audio signals. Audio module 170 may also be used to encode and decode audio signals. In some embodiments, the audio module 170 may be provided in the processor 110 , or some functional modules of the audio module 170 may be provided in the processor 110 .

Speaker 170A, also called "speaker", is used to convert audio electrical signals into sound signals. The electronic device 100 can listen to music through the speaker 170A, or listen to hands-free calls.

Receiver 170B, also called "earpiece", is used to convert audio electrical signals into sound signals. When the electronic device 100 answers a call or a voice message, the voice can be heard by bringing the receiver 170B close to the human ear.

Microphone 170C, also called "microphone" or "microphone", is used to convert sound signals into electrical signals. When making a call or sending a voice message, the user can speak close to the microphone 170C with the human mouth and input the sound signal to the microphone 170C. The electronic device 100 may be provided with at least one microphone 170C. In other embodiments, the electronic device 100 may be provided with two microphones 170C, which in addition to collecting sound signals, may also implement a noise reduction function. In other embodiments, the electronic device 100 can also be provided with three, four or more microphones 170C to collect sound signals, reduce noise, identify sound sources, and implement directional recording functions, etc.

The headphone interface 170D is used to connect wired headphones. The headphone interface 170D may be a USB interface 130, or may be a 3.5mm open mobile terminal platform (OMTP) standard interface, or a Cellular Telecommunications Industry Association of the USA (CTIA) standard interface.

The pressure sensor 180A is used to sense pressure signals and can convert the pressure signals into electrical signals. In some embodiments, pressure sensor 180A may be disposed on display screen 194 .

The gyro sensor 180B may be used to determine the motion posture of the electronic device 100 .

Air pressure sensor 180C is used to measure air pressure. In some embodiments, the electronic device 100 calculates the altitude through the air pressure value measured by the air pressure sensor 180C to assist positioning and navigation.

Magnetic sensor 180D includes a Hall sensor.

The acceleration sensor 180E can detect the acceleration of the electronic device 100 in various directions (generally three axes).

Distance sensor 180F for measuring distance.

Proximity light sensor 180G may include, for example, a light emitting diode (LED) and a light detector,

The ambient light sensor 180L is used to sense ambient light brightness.

Fingerprint sensor 180H is used to collect fingerprints.

Temperature sensor 180J is used to detect temperature.

Touch sensor 180K, also known as "touch device". The touch sensor 180K can be disposed on the display screen 194. The touch sensor 180K and the display screen 194 form a touch screen, which is also called a "touch screen".

Bone conduction sensor 180M can acquire vibration signals.

The buttons 190 include a power button, a volume button, etc. Key 190 may be a mechanical key. It can also be a touch button. The electronic device 100 may receive key inputs and generate key signal inputs related to user settings and function control of the electronic device 100 .

The motor 191 can generate vibration prompts. The motor 191 can be used for vibration prompts for incoming calls and can also be used for touch vibration feedback.

The indicator 192 may be an indicator light, which may be used to indicate charging status, power changes, or may be used to indicate messages, missed calls, notifications, etc.

The SIM card interface 195 is used to connect a SIM card. The SIM card can be connected to or separated from the electronic device 100 by inserting it into the SIM card interface 195 or pulling it out from the SIM card interface 195 .

Based on the hardware structure of the electronic device 100 shown in FIG. 3 , the positioning method of the electronic device 100 of the present application will be described in detail through FIG. 4 .

Specifically, taking the electronic device 100 as a mobile phone 100 as an example, the positioning method in FIG. 4 of this application can be implemented by the processor 110 of the mobile phone 100 executing relevant programs. As shown in Figure 4, a positioning method provided according to a specific embodiment of the present application includes the following steps.

S401: Call the positioning service or enable positioning service security detection to start GNSS spoofing detection.

In the embodiment of the present application, the positioning service here can be a navigation application installed on the mobile phone 100. The user can click the icon of the navigation application to start the navigation application. The navigation application performs positioning by calling the positioning service of the mobile phone 100, for example: the GPS module of the mobile phone 100. service, when the mobile phone 100 detects that the navigation application starts to call the positioning service, the mobile phone 100 can start GNSS spoofing detection. In other embodiments, the user can also enable the location service security detection function of the mobile phone 100. The location service security detection here can be a system service set in the operating system of the mobile phone 100. When the mobile phone 100 detects that the location service security detection is enabled, At this time, the mobile phone 100 can start GNSS spoofing detection.

S402: Identify the navigation satellite number corresponding to the GNSS signal currently used in the process of using the positioning service.

In this embodiment of the present application, the navigation satellite number here may be a pseudo-random noise code, that is, a navigation satellite PRN code. When the mobile phone 100 calls the positioning service, the mobile phone 100 can obtain the navigation satellite number corresponding to the GNSS signal, which is the navigation satellite PRN code carried by the GNSS signal. It is understandable that the navigation satellite PRN codes here are public. The spoofing device can generate and send a spoofing signal similar to the real GNSS signal based on the desired PVT spoofing result and the corresponding ephemeris data.

It can be understood that when the navigation application of the mobile phone 100 calls the positioning service, the mobile phone 100 needs to obtain the GNSS signals of at least four different navigation satellites from the satellite navigation system 200. That is to say, the mobile phone 100 will also recognize at least four different navigation satellites at the same time. Different navigation satellite numbers.

S403: Track and collect the data sequence of the signal power of the GNSS signal corresponding to the navigation satellite number.

In the embodiment of the present application, when the navigation application of the mobile phone 100 calls the positioning service (one of the PVT services), the mobile phone 100 needs to obtain at least four different GNSS signals from the satellite navigation system 200, that is, four sets of For different GNSS signal data sequences, the mobile phone 100 can track the GNSS signals of at least four different navigation satellites according to the navigation satellite numbers corresponding to the GNSS signals, and obtain at least four GNSS signals from at least four different navigation satellites within a preset time period. Data sequence of signal power of GNSS signals.

It can be understood that if the GNSS signal is a real signal, the at least four different GNSS signals may be from at least four different navigation satellites; if the GNSS signal is a spoofing signal, the at least four different GNSS signals may be from the same or Spoofing signals from multiple spoofed devices.

S404: After collecting data after a preset time period, obtain a data sequence of signal powers of multiple GNSS signals.

In this embodiment of the present application, the preset time period here can be set to, for example, 10 seconds. It can be understood that the preset time period can also be of other lengths, and there is no limitation here.

S405: While collecting GNSS signals, simultaneously collect the inertial navigation data of the mobile phone 100.

In this embodiment of the present application, the inertial navigation data here may be data obtained through an inertial measurement unit (IMU) of the mobile phone 100. For example, the inertial navigation data may include the speed, acceleration, direction, etc. of the mobile phone 100. The inertial measurement unit of the mobile phone 100 may include the gyro sensor 180B and the acceleration sensor 180E of the mobile phone 100. While the mobile phone 100 collects GNSS signals, the mobile phone 100 may collect the speed, acceleration and direction of the mobile phone 100 through the gyro sensor 180B and the acceleration sensor 180E. wait.

S406: Perform low-pass filtering on the data sequences of signal powers of multiple GNSS signals to remove high-frequency noise.

In the embodiment of the present application, the mobile phone 100 can perform low-pass filtering on the data sequence of the signal power of the GNSS signals of multiple navigation satellites to remove noise with high signal power in the frequency band.

S407: Perform correlation measurement on the filtered data sequences of the signal powers of multiple GNSS signals, obtain the correlation coefficients between the signal powers of the GNSS signals of multiple navigation satellites, and obtain the correlation coefficients of multiple correlation coefficients mean.

In the embodiment of the present application, the correlation measurement method for the data sequence of the signal power of the GNSS signal may be to calculate the correlation coefficient of the data sequence of the signal power of the GNSS signal. The correlation coefficient may include: Pearson correlation coefficient, Pillman correlation coefficient and Kendall correlation coefficient, etc.

Take the Pearson correlation coefficient as an example. The Pearson correlation coefficient is used to measure the linear correlation between two variables. The Pearson correlation coefficient has a value between +1 and -1, where 1 represents a total positive linear correlation, 0 represents a nonlinear correlation, and -1 represents a total negative linear correlation. The calculation formula corresponding to the Pearson correlation coefficient ρ is as follows:

Among them, _X and Y respectively represent any two signal powers in the data sequence of the signal power of multiple GNSS signals, σ covariance between.

It can be understood that in the process of calling the positioning service by the navigation application of the mobile phone 100, the mobile phone 100 obtains the data sequence of the signal power of at least four GNSS signals, and then the mobile phone 100 can obtain the correlation between the signal powers of at least four GNSS signals. coefficient.

It can be understood that in order to further determine the correlation between GNSS signals, the average correlation coefficient between pairs of at least four GNSS signals can be calculated, for example, taking signal i and signal j among at least four GNSS signals as an example. , calculate the average correlation coefficient of signal i and signal j through the following formula.

Where N represents the number of collected GNSS signals.

It can be understood that the above formula can be saved in the internal memory of the mobile phone 100. While the positioning service of the mobile phone 100 collects the GNSS signal, the mobile phone 100 can calculate the GNSS signal in real time according to the saved formula to determine whether the GNSS signal is a real signal or not. Spoofing signals.

In another embodiment of the present application, taking the correlation coefficient of the data sequence of the signal power of the GNSS signal as the Spearman correlation coefficient as an example, the Spearman correlation coefficient is used to utilize the rank size of the signal power of the two GNSS signals. For linear correlation analysis, the calculation formula corresponding to the Spearman correlation coefficient ρ is as follows:

where x′ and y′ represent the ranks of the collected GNSS signals.

S408: Based on the synchronously collected inertial navigation data, identify the motion state of the mobile phone 100 during the signal power collection of the GNSS signal.

In the embodiment of the present application, the process of determining the motion state of the mobile phone 100 may include: the mobile phone 100 may obtain the navigation coordinate system based on the mobile phone 100 through the gyroscope sensor, stabilize the measurement axis of the acceleration sensor in the navigation coordinate system, and give The direction and attitude angle of the mobile phone 100 are obtained, and then the acceleration of the mobile phone 100 is measured through the acceleration sensor. The speed of the mobile phone 100 can be obtained based on the integral operation during the acquisition period.

It can be understood that the mobile phone 100 can compare the obtained speed with the speed threshold to determine the motion state of the mobile phone 100 . For example, the speed of the mobile phone 100 can be 2 meters/second. If the speed threshold is 1 meter/second, the mobile phone 100 can determine that the mobile phone 100 is in a moving state; otherwise, it can be determined that the mobile phone 100 is in a stationary state.

S409: Determine a preset threshold corresponding to the motion state according to the motion state of the mobile phone 100.

In this embodiment of the present application, if the mobile phone 100 is in motion, it will affect the correlation coefficient between the signal powers of the multiple GNSS signals calculated in step S407, thereby affecting the average correlation coefficient of the multiple correlation coefficients. Therefore, the preset threshold corresponding to the motion state of the mobile phone 100 can be set in combination with the motion state of the mobile phone 100 identified in step S408. For example: the preset threshold corresponding to the stationary state can be 0.5, and the preset threshold corresponding to the moving state can be 0.8.

S410: Compare the average correlation coefficient with the preset threshold corresponding to the motion state of the mobile phone 100 to determine whether the GNSS signal is a real signal or a spoofing signal.

If the correlation coefficient is lower than the preset threshold, it means that the correlation between the GNSS signals collected by the mobile phone 100 is low, and the collected GNSS signals are determined to be real signals. If the correlation coefficient is higher than the preset threshold, it means that the correlation between the GNSS signals collected by the mobile phone 100 is low. If the correlation between GNSS signals is high, it is determined that the collected GNSS signal is a spoofing signal.

In the embodiment of the present application, if the mobile phone 100 determines that the collected GNSS signal is a real signal, the mobile phone 100 can allow the application program to call the positioning service to complete the function corresponding to the application program; if the mobile phone 100 determines that the collected GNSS signal is a fraudulent signal, If the signal is spoofed, step S411 is executed. The mobile phone 100 can feed back the detection result of the spoofed signal to the application, prompt the user who opens the application, or disable the GNSS positioning service and instead call other positioning services, such as network positioning.

For example, the mobile phone 100 is in a stationary state. If the average correlation coefficient of the GNSS signal obtained by the mobile phone 100 through step S407 is 0.0099, and the preset threshold corresponding to the stationary state can be 0.5, then the mobile phone 100 can determine that the collected GNSS signal is a real signal. If the average value of the correlation coefficient of the GNSS signals obtained by the mobile phone 100 in step S407 is 0.6534, the mobile phone 100 can determine that the collected GNSS signals are spoofing signals. Similarly, the mobile phone 100 is in a moving state. If the average correlation coefficient of the GNSS signal obtained by the mobile phone 100 through step S407 is 0.0385, and the preset threshold corresponding to the moving state can be 0.8, then the mobile phone 100 can determine that the collected GNSS signal is a real signal. , if the average correlation coefficient of the GNSS signal obtained by the mobile phone 100 through step S407 is 0.9015, the mobile phone 100 can determine that the collected GNSS signal is a spoofing signal.

S411: If the GNSS signal is identified as a spoofing signal, it will be fed back to the application that calls the positioning service.

In the embodiment of this application, if the mobile phone 100 recognizes that the GNSS signal obtained by the positioning service is a spoofing signal, the mobile phone 100 can disable the GNSS positioning service (turn off the positioning service, that is, turn off the currently used positioning service), and instead call other positioning services. , such as network positioning, and prompts the user in the user interface of the mobile phone 100 to re-verify the security of the GNSS positioning service. In another embodiment of the present application, the mobile phone 100 can also prompt on the screen that the satellite signal accepted by the positioning service is incorrect or prompt to restart the positioning service so that the positioning service can obtain the real signal.

If the mobile phone 100 recognizes that the GNSS signal is a real signal, the mobile phone 100 can use the positioning service (such as navigation service) normally and obtain the positioning result of the positioning service. For example, taking the positioning service as a navigation service as an example, the positioning result can be navigation Navigation routes provided by the service. For another example, the positioning result may also be the map location provided by the positioning service.

It can be understood that the numerical values described in Figure 4 are exemplary. In the embodiment of the present application, other numerical values can also be used, and there is no limitation here.

It can be seen that using the positioning method shown in Figure 4 above, when the mobile phone 100 needs to call the positioning service or when the mobile phone 100 detects that the application of the mobile phone 100 calls the positioning service, the mobile phone 100 can automatically start spoofing signal detection, ensuring that the mobile phone 100 100 can receive real GNSS signals, ensuring the safety of mobile phone 100 using positioning services.

The positioning method of the mobile phone 100 according to another embodiment of the present application will be described in detail below with reference to FIGS. 5 and 6 .

Specifically, the positioning method in Figure 5 of this application can be implemented by the processor 110 of the mobile phone 100 executing relevant programs. The difference from the positioning method shown in FIG. 4 is that in the positioning method shown in FIG. 5 , the similarity measurement neural network that has been trained in advance can be stored in the storage area of the mobile phone 100 . When the mobile phone 100 calls the positioning service, after a preset time period, the data sequence of the signal power of multiple GNSS signals corresponding to the navigation satellite numbers (i.e., sat ₁ to sat _N in Figure 5) and the motion status of the mobile phone 100 are collected. , input the obtained data sequence of the signal power of the GNSS signals of multiple navigation satellites into the similarity measurement neural network (CNN network) corresponding to the motion state of the mobile phone 100, and obtain the output result of the similarity measurement neural network, the output result here It can be a similarity matrix obtained from the data sequence of the signal power of GNSS signals of multiple navigation satellites; calculate the similarity matrix to obtain the similarity coefficient mean cc _mean corresponding to the similarity matrix,

Compare the mean value of the similarity coefficient with a preset threshold corresponding to the motion state of the mobile phone 100 to determine whether the GNSS signal received by the mobile phone 100 is a real signal or a spoofed signal.

As shown in Figure 6, a positioning method provided according to a specific embodiment of the present application includes the following steps.

S601: Call the positioning service or enable positioning service security detection to start GNSS spoofing detection.

In the embodiment of the present application, step S601 here is similar to step S401 in Figure 4. For example, the GPS module of the mobile phone 100 performs positioning services. When the mobile phone 100 detects that the navigation application starts to call the positioning service, the mobile phone 100 can start GNSS spoofing detection. . In another embodiment of the present application, the user can also enable the location service security detection function of the mobile phone 100. The location service security detection here can be a system service set in the operating system of the mobile phone 100. When the mobile phone 100 detects that the location service security is enabled, During detection, the mobile phone 100 can start GNSS spoofing detection.

S602: Identify the navigation satellite number corresponding to the GNSS signal currently used in the process of using the positioning service.

In the embodiment of the present application, step S602 here is similar to step S402 in Figure 4. During the process of calling the positioning service by the mobile phone 100, the mobile phone 100 can obtain the navigation satellite number corresponding to the GNSS signal, that is, the navigation satellite PRN carried by the GNSS signal. code.

It can be understood that when the navigation application of the mobile phone 100 calls the positioning service, the mobile phone 100 needs to obtain the GNSS signals of at least four different navigation satellites from the satellite navigation system 200. That is to say, the mobile phone 100 will also recognize at least four different navigation satellites at the same time. Different navigation satellite numbers, namely navigation satellite PRN codes.

S603: Track and collect the data sequence of the signal power of the GNSS signal corresponding to the navigation satellite number.

In the embodiment of the present application, step S603 here is similar to step S403 in Figure 4. In the process of calling the positioning service by the navigation application of the mobile phone 100, the mobile phone 100 needs to obtain data sequences of the signal power of at least four different GNSS signals. That is, the data sequence of the signal power of four different GNSS signals.

S604: After collecting data after a preset time period, obtain a data sequence of signal powers of multiple GNSS signals.

In this embodiment of the present application, step S604 here is similar to step S404 in FIG. 4 , and the preset time period here can be set to, for example, 10 seconds. It can be understood that the preset time period can also be of other lengths, and there is no limitation here.

S605: While collecting GNSS signals, simultaneously collect the inertial navigation data of the mobile phone 100.

In the embodiment of the present application, step S605 here is similar to step S405 in Figure 4. While the mobile phone 100 collects GNSS signals, the mobile phone 100 can collect the speed, acceleration, direction, etc. of the mobile phone 100 through the gyroscope sensor 180B and the acceleration sensor 180E. .

S606: Perform low-pass filtering on the data sequences of signal powers of multiple GNSS signals to remove high-frequency noise.

In the embodiment of the present application, step S606 here is similar to step S406 in FIG. 4 . The mobile phone 100 can perform low-pass filtering on the data sequence of the signal power of multiple GNSS signals to remove noise with high signal power in the frequency band.

S607: Based on the synchronously collected inertial navigation data, identify the motion state of the mobile phone 100 during the signal power collection of the GNSS signal.

In the embodiment of the present application, step S607 here is similar to step S408 in Figure 4. The mobile phone 100 can obtain the navigation coordinate system based on the mobile phone 100 through the gyroscope sensor, and stabilize the measurement axis of the acceleration sensor in the navigation coordinate system. The direction and attitude angle of the mobile phone 100 are given, and then the acceleration of the mobile phone 100 is measured through the acceleration sensor. The speed of the mobile phone 100 can be obtained based on the integral operation during the acquisition period.

S608: Input the filtered data sequence of the signal power of multiple GNSS signals into the similarity measurement neural network corresponding to the motion state of the mobile phone 100, and obtain the mean value of the correlation coefficient output by the similarity measurement neural network.

In the embodiment of the present application, the motion state of the mobile phone 100 can be divided into a static state and a moving state. Correspondingly, the mobile phone 100 can also store similarity measurement neural networks corresponding to the stationary state and the moving state respectively. The process of training the similarity measure neural network corresponding to the stationary state and the moving state will be introduced in detail below.

S609: Determine a preset threshold corresponding to the motion state according to the motion state of the mobile phone 100.

In this embodiment of the present application, step S609 here is similar to step S409 in FIG. 4 . For example, the preset threshold corresponding to the stationary state may be 0.5, and the preset threshold corresponding to the moving state may be 0.8.

S610: Compare the average correlation coefficient with the preset threshold corresponding to the motion state of the mobile phone 100 to determine whether the GNSS signal is a real signal or a spoofing signal.

In the embodiment of the present application, step S610 here is similar to step S410 in Figure 4. If the mobile phone 100 determines that the collected GNSS signal is a real signal, the mobile phone 100 can allow the application to call the positioning service to complete the function corresponding to the application; if the mobile phone 100 100 determines that the collected GNSS signal is a spoofing signal, and then executes step S611. The mobile phone 100 can feed back the detection result of the spoofing signal to the application, prompt the user who opens the application, or prohibit the application from calling positioning services.

S611: Identify the GNSS signal as a spoofing signal and feed it back to the application that calls the positioning service.

In the embodiment of the present application, step S611 here is similar to step S411 in Figure 4. If the mobile phone 100 recognizes that the GNSS signal obtained by the positioning service is a spoofing signal, the mobile phone 100 can disable the GNSS positioning service and instead call other positioning services. Such as network positioning, and prompts the user in the user interface of the mobile phone 100 to re-verify the security of the GNSS positioning service.

The process of training the similarity measurement neural network corresponding to the static state and the moving state described in step S608 of Figure 6 is introduced below through Figure 7, including:

S701: Obtain a data set of sequence data of signal power of real GNSS signals.

In the embodiment of the present application, when the mobile phone 100 is in the stationary state and the moving state, sequence data collection of the signal power of the GNSS signal is performed, and a data set corresponding to the stationary state and the moving state is constructed.

S702: Perform low-pass filtering on the data set to filter out high-frequency noise in the signal.

In the embodiment of the present application, low-pass filtering can be performed on the data sequence of the signal power of the GNSS signals in the data set to remove noise with high frequency bands in the signal power.

S703: Use the spoofing signals collected in the stationary state and the moving state and the real GNSS signal data sets to conduct similarity measurement neural network training.

In the embodiment of the present application, the training method of the similarity measurement neural network may include: collecting spoofing signals collected in the stationary state and moving state and real GNSS signals; during training, the spoofing signals collected in the stationary state and moving state and Real GNSS signals are input into the similarity measurement neural network, and feedback iteration and other methods are used for similarity measurement neural network training. The input of the similarity measurement neural network here can be the spoofing signals collected in the stationary state and the moving state as well as the real GNSS signals. The output of the similarity measurement neural network is the similarity matrix between the input multi-dimensional time series.

S704: Deploy the trained similarity measure neural network corresponding to the stationary state and the moving state on the mobile phone 100.

In the embodiment of this application, taking the operating system of mobile phone 100 as Android system as an example, the similarity measurement neural network can be packaged into an apk format and installed in the operating system of mobile phone 100. When mobile phone 100 runs GNSS spoofing detection, it can be The collected GNSS signals are input to a similarity measure neural network deployed within the mobile phone 100 .

After introducing the signal detection method provided by the embodiment of the present application through Figures 4 to 7, the present application will be introduced below through Figure 8. Please implement another signal detection method in the embodiment, as shown in Figure 8. The positioning method provided according to a specific implementation of the present application includes the steps shown below.

S801: Select the GNSS signal used in the current positioning solution.

In this embodiment of the present application, the GNSS signal here may be the GNSS signal used in the currently used positioning service process. It can be understood that the solution here can mean analyzing and calculating the GNSS signal used by the currently used positioning service.

S802: Track and record the fading data of GNSS signal reception strength over time.

In this embodiment of the present application, the fading data here may be a data sequence that tracks the satellite signal according to the navigation satellite number corresponding to the satellite signal and obtains the signal power of the satellite signal within a preset time period.

S803: Determine whether the data collection time is greater than the preset time period.

In the embodiment of this application, the preset time period here can be set to, for example, 10 seconds. If the data collection time does not reach the preset time period, continue to execute step S802; if the data collection time reaches the preset time period, execute S804. , preprocess the collected satellite signals.

S804: Data preprocessing.

Step S804 here is similar to step S406 in FIG. 4 . The mobile phone 100 can perform preprocessing such as low-pass filtering on multiple satellite signals to remove high-frequency noise in the satellite signals.

S805: Analyze and quantify time series correlation.

In the embodiment of the present application, correlation measurement is performed on multiple preprocessed satellite signals, correlation coefficients between the multiple satellite signals are obtained, and the average correlation coefficient of the multiple correlation coefficients is obtained.

In this embodiment of the present application, the method of measuring the correlation of satellite signals may be to calculate the correlation coefficient of the navigation satellite signal. The correlation coefficient may include: Pearson correlation coefficient, Spearman correlation coefficient, Kendall correlation coefficient, etc.

S806: Determine whether the correlation coefficient is greater than the preset threshold.

In this embodiment of the present application, if the correlation coefficient is lower than the preset threshold, it means that the collected satellite signal is a real signal; if the correlation coefficient is higher than the preset threshold, it is determined that the collected GNSS signal is a spoofing signal.

It should be understood that, although the terms "first," "second," etc. may be used herein to describe various features, these features should not be limited by these terms. These terms are used solely for purposes of distinction and are not to be construed as indicating or implying relative importance. For example, a first feature could be termed a second feature, and similarly a second feature could be termed a first feature, without departing from the scope of example embodiments.

Furthermore, various operations will be described as multiple discrete operations in a manner that is most helpful in understanding the illustrative embodiments; however, the order of description should not be construed to imply that these operations are necessarily dependent on the order of description, many of which Operations can be performed in parallel, concurrently, or simultaneously. Additionally, the order of operations can be rearranged. The process may be terminated when the described operations are completed, but may also have additional operations not included in the figures. The processing may correspond to a method, function, procedure, subroutine, subroutine, or the like.

References in the specification to "one embodiment," "an embodiment," "an illustrative embodiment," etc., mean that the described embodiment may include a particular feature, structure, or property, but that each embodiment may or need not include certain features, structures, or properties. characteristics, structure or properties. Furthermore, these phrases are not necessarily referring to the same embodiment. Furthermore, when particular features are described in connection with specific embodiments, the knowledge of those skilled in the art can influence the combination of these features with other embodiments, whether or not these embodiments are explicitly described.

The terms "includes,""has," and "includes" are synonyms unless the context dictates otherwise. Phrase "A/B" means "A or B". The phrase "A and/or B" means "(A), (B) or (A and B)".

As used herein, the term "module" may refer to, be a part of, or include: memory (shared, dedicated, or group) for running one or more software or firmware programs, an Application Specific Integrated Circuit (ASIC), Electronic circuits and/or processors (shared, dedicated, or group), combinational logic circuits, and/or other suitable components that provide the functionality described.

In the drawings, some structural or methodological features may be shown in specific arrangements and/or orders. However, it should be understood that such specific arrangement and/or ordering is not required. Rather, in some embodiments, the features may be illustrated in a manner and/or order different than that shown in the illustrative figures. In addition, the inclusion of structural or method features in a particular drawing does not mean that all embodiments need to include such features. In some embodiments, these features may not be included, or these features may be combined with other features.

The embodiments of the present application are described in detail above with reference to the accompanying drawings. However, the use of the technical solutions of the present application is not limited to the various applications mentioned in the embodiments of the present patent. Various structures and modifications can be easily made with reference to the technical solutions of the present application. implementation to achieve the various beneficial effects mentioned in this article. Various changes made within the scope of knowledge possessed by those of ordinary skill in the art without departing from the purpose of this application shall fall within the scope of the patent covered by this application.

Claims

A positioning method applied to electronic equipment, characterized in that the method includes:

In response to the electronic device initiating the positioning service, obtain a signal power change sequence of multiple satellite signals within a preset time period;

Based on the signal power change sequence of the multiple satellite signals, determine whether the fading characteristics between the signals of the multiple satellite signals within the preset time period meet the positioning requirements;

Corresponding to the fading characteristics of multiple satellite signals within the multiple preset time periods meeting the positioning requirements, a positioning result generated based on the multiple satellite signals is obtained.
The method according to claim 1, characterized in that, obtaining the signal power change sequence of multiple satellite signals within a preset time period includes:

Identify the navigation satellite numbers corresponding to the plurality of satellite signals used by the positioning service within the preset time period;

Track the signal power changes of the multiple satellite signals within the preset time period according to the navigation satellite number, and obtain the signal power change sequence of the multiple satellite signals.
The method according to claim 1, characterized in that the positioning requirements include:

The average value of the correlation coefficient between the fading characteristics of the signal power change sequence of each of the satellite signals within the preset time period is lower than a preset threshold, wherein the correlation coefficient is used to represent the multiple satellite signals The similarity of the fading characteristics between the signal power change sequences of the two satellite signals in the signal power change sequence.
The method of claim 3, wherein the preset threshold is related to a motion state of the electronic device, wherein the motion state is used to indicate that the electronic device is at least in a static state or a moving state. A sort of.
The method according to claim 4, characterized in that the correlation coefficient is obtained through at least one of Pearson correlation coefficient, Spearman correlation coefficient, Kendall correlation coefficient and similarity measure neural network model.
The method according to claim 4, characterized in that the motion state of the electronic device is determined in the following manner:

Determine the speed of the electronic device through the gyro sensor and acceleration sensor of the electronic device;

The motion state of the electronic device is determined according to a comparison result between the speed of the electronic device and a speed threshold.
The method according to claim 1, further comprising:

Corresponding to the fading characteristics of multiple satellite signals within the multiple preset time periods that do not meet the positioning requirements, the user is prompted that the positioning service is abnormal.
The method according to claim 7, wherein the method for prompting the user that the positioning service is abnormal includes at least one of the following:

The electronic device prompts to turn off the positioning service;

The electronic device prompts that the satellite signal received by the positioning service is abnormal;

The electronic device prompts to re-enable the positioning service.
An electronic device, characterized by including:

A processor, configured to execute the positioning method according to any one of claims 1 to 8; and

Memory, which may or may not be coupled to the processor, for storing instructions for execution by the processor.
A computer-readable storage medium, characterized in that the computer-readable storage medium contains instructions that, when executed by a processor of an electronic device, cause the electronic device to implement any one of claims 1 to 8. Describe the positioning method.
A computer program product, characterized by comprising: a computer-readable storage medium containing computer program code for executing the positioning method according to any one of claims 1 to 8.