Combined positioning service framework

Abstract

The invention provides a combined positioning service framework, which belongs to the technical field of information and communication, and comprises three layers: a bottom layer data processing module is deployed at the bottom layer of an operating system, receives original measurement data of a sensor or positioning hardware, caches the original measurement data after adding a local timestamp, and does not analyze data content; the data packaging and combined positioning calculation module is located in an application layer or a service layer, reads original data with a timestamp, executes a combined positioning algorithm to generate a position result, and writes the position result into an output buffer area of the bottom layer module; and the system position service module switches the data source to the output buffer area, obtains a position result, and provides a unified position service for an application program in the system. The invention provides a combined positioning service framework which is low in invasion, high in compatibility and easy to expand, high-precision positioning result seamless access system position service is realized through a layered decoupling architecture, and the positioning robustness and deployment efficiency in a complex environment are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of information and communication technology, and more specifically, to a combined positioning service framework. Background Technology

[0002] In existing integrated positioning technology implementations, the integrated positioning module is typically deployed at the system's bottom layer (such as the driver layer or firmware layer) to directly process raw data from sensors such as GNSS, IMU, and Wi-Fi. While this design helps reduce latency, it has significant limitations: firstly, the underlying implementation struggles to flexibly adapt to diverse fusion algorithms (e.g., in the use of external data, such as map data access); secondly, once the positioning logic is fixed at the bottom layer, subsequent upgrades to include external reference data such as map matching and road constraints often require a complete refactoring of the driver or firmware, resulting in high maintenance costs and poor scalability.

[0003] Of particular note is that backend fusion positioning (such as methods based on factor graph optimization, sliding window, or offline fusion) has demonstrated significant advantages in accuracy and robustness, especially in complex scenarios such as GNSS rejection or signal degradation. However, since its computation typically resides in user space or the service layer, the generated high-precision location results are difficult to efficiently and systematically inject into the operating system's native location service system. Existing solutions lack a loosely coupled, high-throughput, and highly versatile output path, preventing the backend fusion capabilities from being transparently invoked by applications within the system, severely limiting the effectiveness of advanced positioning algorithms in practical systems.

[0004] Therefore, in view of the above situation, there is an urgent need to develop a combined positioning service framework to overcome the shortcomings in current practical applications. Summary of the Invention

[0005] The purpose of this invention is to provide a service framework for combined positioning, which aims to solve the problems mentioned in the background art, such as poor flexibility and difficulty in integrating with system services caused by embedding the combined positioning algorithm at the underlying layer.

[0006] This invention proposes a core concept for a layered, decoupled service framework. This concept decouples raw data acquisition from the positioning algorithm by designing a unified data channel located at the operating system's lower layer, responsible only for adding timestamps and caching. Then, it elevates the data packaging and combined positioning calculation module to the application or service layer, enabling flexible algorithm deployment. Finally, by redirecting the data source of the system's location service module to the output of the aforementioned channel, it achieves seamless and transparent injection of high-precision positioning results into the operating system's native services. This concept ensures that the framework improves positioning performance while maintaining low invasiveness, high compatibility, and easy scalability.

[0007] This invention is implemented as follows: a combined positioning service framework, comprising:

[0008] The underlying data processing module, configured at the operating system level, is used to receive raw measurement data from sensors or positioning hardware. Upon receiving the raw measurement data, it appends a local timestamp and caches the data without parsing the content of the raw measurement data.

[0009] The data packaging and combined positioning calculation module, located in the upper application layer or service layer, is used to read the raw measurement data with timestamps from the underlying data processing module, execute the combined positioning algorithm to generate the location result, and write the location result back to the output buffer provided or managed by the underlying data processing module.

[0010] The system location service module is configured to switch the data source to the output buffer of the underlying data processing module to obtain the location results generated by the data packaging and combination positioning calculation module, and to provide a unified location service to applications within the system.

[0011] Optionally, the underlying data processing module is implemented through a character device or virtual device node, allowing the upper-layer module to perform read and write operations through standard system calls; the character device or virtual device node adopts a zero-copy or memory mapping mechanism to support concurrent access by multiple producers and a single consumer or multiple consumers.

[0012] Optionally, the character device or virtual device node exposes standardized input / output instructions and ioctl control commands to combine the input / output of positioning data, read related settings, dynamically configure timestamp type, buffer size, data format version, and algorithm feedback parameters.

[0013] Optionally, the local timestamp is a monotonically increasing timestamp generated based on the system's monotonic clock, used to ensure time alignment of multi-source sensor data.

[0014] Optionally, the underlying data processing module provides two sets of logically isolated, physically coexisting independent encapsulated interfaces, namely the raw measurement data input interface and the combined positioning result output interface, corresponding to independent circular buffers or memory-mapped areas, and distinguished by different file descriptors, ioctl control commands, or read / write direction semantics.

[0015] Optionally, the combined positioning algorithm strategy includes one or more combinations of GNSS / IMU tightly coupled or loosely coupled filtering, Wi-Fi / Bluetooth fingerprint-assisted positioning, visual / laser odometry fusion, and high-precision map matching to enhance positioning.

[0016] Optionally, the system location service module is a native location service component of the operating system, which redirects the data source to the output buffer of the underlying data processing module through configuration file overriding, service binding hijacking, HAL layer proxy, or runtime dynamic link library interception mechanisms.

[0017] Optionally, the underlying data processing module adds timestamps by reducing intermediate modules to align the time of each data input source, ensuring that the sensor data is strictly aligned with the system clock.

[0018] Optionally, the raw measurement data comes from one or more heterogeneous sensors, including GNSS, IMU, wheel speedometer, Wi-Fi, or Bluetooth.

[0019] The combined positioning service framework provided by this invention has the following beneficial effects:

[0020] By constructing a layered and decoupled combined positioning service framework, the underlying cache, the upper-layer flexible and replaceable combined positioning calculation and system location service are seamlessly connected. Under the premise of almost no modification to the existing operating system architecture, high-precision and highly adaptable positioning capabilities are integrated. It not only supports the fusion of multi-source heterogeneous data and the introduction of external information (such as road data), which significantly improves the positioning robustness in weak signal or no GNSS scenarios, but also has the advantages of low intrusion, easy deployment and cross-platform, effectively taking into account system compatibility, algorithm flexibility and engineering implementation efficiency.

[0021] In summary, this invention provides a low-intrusion, highly compatible, and easily scalable combined positioning service framework. Through a layered and decoupled architecture, it enables seamless integration of high-precision positioning results into the system's location services, significantly improving positioning robustness and deployment efficiency in complex environments.

[0022] Other features and advantages of the invention will become clear from the following detailed description of exemplary embodiments of the invention with reference to the accompanying drawings. Attached Figure Description

[0023] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments of the invention and, together with their description, serve to explain the principles of the invention.

[0024] Figure 1 This is a schematic diagram of the combined positioning service framework provided in an embodiment of the present invention. Detailed Implementation

[0025] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0026] The following section describes, with reference to the accompanying drawings, a service framework for combined positioning according to an embodiment of the present invention.

[0027] like Figure 1 As shown, a combined positioning service framework provided in one embodiment of the present invention includes:

[0028] The underlying data processing module, configured at the operating system level, is used to receive raw measurement data from sensors or positioning hardware. Upon receiving the raw measurement data, it appends a local timestamp and caches it without parsing the content of the raw measurement data, thus achieving a transparent transmission effect and facilitating protocol expansion.

[0029] The data packaging and combined positioning calculation module (including a combined data packaging module, or a module that directly supports data formats) can be located in the upper application layer or service layer. It is used to read the raw measurement data with timestamps from the underlying data processing module, execute the combined positioning algorithm to generate the location result, and write the location result back to the output buffer provided or managed by the underlying data processing module.

[0030] The system location service module is configured to switch the data source to the output buffer of the underlying data processing module to obtain the location results generated by the data packaging and combination positioning calculation module, and to provide a unified location service to applications within the system.

[0031] In one embodiment, the underlying data processing module is implemented through a character device or virtual device node, allowing upper-layer modules to perform read and write operations via standard system calls. This design does not simply follow the traditional device-driven model; instead, it abstracts the combined positioning data input and output into a unified, hardware-independent "positioning data channel" interface. This allows the injection of raw measurement data and the output of fused position results to be completed through the same device node, but logically separated into independent input and output circular buffers. This achieves physical coexistence and logical isolation of input / output paths in kernel space.

[0032] Furthermore, this character device employs a zero-copy or memory-mapped mechanism, supporting concurrent access from multiple producers to a single consumer or multiple consumers (ensuring consistent access to the shared buffer through kernel semaphores, spinlocks, or atomic operations), and ensuring strict alignment of sensor data with the system clock through a kernel-level timestamp synchronization mechanism. More importantly, the device node exposes standardized ioctl control commands for dynamically configuring timestamp type, buffer size, data format version, and algorithm feedback parameters. This allows the upper-layer data packaging and fusion positioning calculation modules to access and control the positioning data stream consistently across different operating systems such as Android, Linux, and RTOS without being aware of underlying hardware differences, significantly improving the portability of the backend fusion algorithm and system integration efficiency.

[0033] Understandably, regarding zero-copy or memory-mapped mechanisms: depending on the system memory layout and performance requirements, a zero-copy mechanism can be chosen to reduce CPU overhead, or a memory-mapped mechanism can be chosen to simplify user space access.

[0034] Preferably, the underlying data processing module should also include an exception handling mechanism. For example, when the input data rate exceeds the buffer capacity, the module can handle the buffer overflow according to a preset strategy (such as discarding the oldest data or notifying the producer to reduce the frequency); when an abnormal interruption of the sensor data stream or a severe change in the timestamp is detected, a notification can be sent to the upper-layer module through the ioctl command or system log so that the data packaging and combination positioning calculation module can promptly enable the degradation strategy or perform a state reset.

[0035] In one embodiment, the local timestamp is a monotonically increasing timestamp used to ensure time alignment of multi-source sensor data. Specifically, the local timestamp uses a monotonically increasing timestamp generated based on the system's monotonic clock, rather than relying on a real-time clock susceptible to system time adjustments. This timestamp can be used as a time calibration basis for multiple devices. This timestamp is injected the moment the raw measurement data enters the underlying data processing module, ensuring that all data from heterogeneous sensors such as GNSS, IMU, wheel speedometer, Wi-Fi, or Bluetooth are anchored to the same continuous and irreversible time reference. Since the monotonic clock is unaffected by external interference such as NTP calibration, user manual time adjustment, or daylight saving time switching, it effectively avoids timing discrepancies caused by time jumps or rollbacks in multi-source data. This provides a highly reliable time alignment foundation for subsequent combined positioning algorithms (especially tightly coupled filtering or optimization algorithms relying on microsecond-level synchronization), significantly improving trajectory continuity and positioning accuracy.

[0036] In one embodiment, the data packaging and combined positioning calculation module supports dynamic replacement and can load different combined positioning algorithms according to the application scenario, including but not limited to one or more combinations of GNSS / IMU fusion, Wi-Fi assisted positioning, and map matching enhanced positioning.

[0037] Specifically, the data packaging and combined positioning calculation module is implemented as a plug-in or dynamic link library (DLL / SO) module, supporting the dynamic loading, unloading, or switching of different combined positioning algorithm strategies at runtime based on the current application scenario, environmental awareness status, or positioning performance requirements. These algorithm strategies include, but are not limited to: GNSS / IMU tightly coupled or loosely coupled filtering, Wi-Fi / Bluetooth fingerprint-assisted positioning, visual / laser odometry fusion, high-precision map matching-enhanced positioning, and multimodal fusion optimization models. The tightly coupled method has very high time requirements, and this solution, in particular, helps ensure the alignment requirements of the tightly coupled approach.

[0038] Furthermore, this module ensures that different algorithm components are plug-and-play through a unified algorithm interface specification (such as predefined data input formats, output structures, and callback mechanisms), without requiring modification to the underlying data path or upper-layer location service logic. For example, it automatically enables map constraints and IMU dead reckoning in urban canyon environments, switches to a Wi-Fi + Bluetooth fusion mode in indoor scenarios, and prioritizes a high-precision GNSS / IMU combination in open areas. This dynamic adaptation mechanism not only significantly improves the system's robustness and accuracy continuity in complex heterogeneous environments but also provides an open and standardized technical path for subsequent algorithm iterations and third-party extensions.

[0039] Preferably, the data packaging and combined positioning calculation module may further include a lightweight policy scheduler. This scheduler dynamically determines whether to load, unload, or switch different algorithm plugins based on real-time input sensor data quality (such as GNSS signal-to-noise ratio and visible satellite count), environmental context information (such as indoor / outdoor status provided by the map module), or application-specified accuracy / power consumption requirements. For example, in open environments with good GNSS signals, the GNSS / IMU loosely coupled algorithm is primarily run; when entering urban canyons that degrade GNSS signals, the weights of Wi-Fi fingerprint matching and map matching algorithms are automatically increased; in completely GNSS-free indoor environments, the system switches to a fusion positioning mode primarily based on IMU, Wi-Fi, and Bluetooth.

[0040] In one embodiment, the system location service module is a native location service component of the operating system (such as LocationManager in Android, Geoclue in Linux, or a general POSIX-compliant location service framework). By modifying its data input source to point to the output buffer of the underlying data processing module, the combined location results can be used without modifying the upper-layer application.

[0041] Specifically, by lightweight redirecting its data source input path—that is, replacing its original default positioning engine (such as GNSS HAL or network positioning plugin) with an output buffer pointing to the underlying data processing module—high-precision combined positioning results are seamlessly injected into the system-level location service pipeline. This redirection can be achieved through mechanisms such as configuration file overriding, service binding hijacking, HAL layer proxy, or runtime dynamic link library interception, without modifying the operating system kernel, location service core logic, or any upper-layer application code. As a result, all applications that rely on standard location APIs (such as request Location Updates) can transparently and seamlessly obtain the enhanced location information generated by the backend combined positioning algorithm, significantly lowering the threshold for implementing high-precision positioning capabilities and avoiding fragmentation and maintenance costs caused by application adaptation.

[0042] In one embodiment, the underlying data processing module provides independently encapsulated input and output interfaces, which are used to receive raw measurement data and output combined positioning results, respectively, thereby decoupling the input path from the output path.

[0043] Specifically, the underlying data processing module provides two logically isolated but physically coexisting independent encapsulated interfaces: one is a raw measurement data input interface, used to receive raw observation data from multimodal sensors such as GNSS, IMU, wheel speedometer, and wireless signal sources; the other is a combined positioning result output interface, dedicated to providing the system location service module with high-precision location information generated after upper-layer fusion calculation. Although these two interfaces can share the same character device or virtual device node, they correspond to independent ring buffers or memory-mapped regions at the kernel buffer level, and are distinguished by different file descriptors, ioctl command sets, or read / write direction semantics, thereby achieving complete decoupling of the input and output paths at the driver level. This design avoids timing interference and parsing ambiguity caused by read / write contention, data mixing, or protocol coupling in traditional single-channel solutions. It not only ensures the integrity and timeliness of the raw data, but also ensures that the combined positioning results can be consumed by the system service in a low-latency and highly reliable manner, while reserving an architectural foundation for future expansion to multi-algorithm parallel output or multi-client subscription mechanisms.

[0044] As can be seen from the above description, the service framework of this combined positioning is divided into three parts:

[0045] The first part is the data processing module of the underlying software layer. When this module receives raw measurement data from sensors or positioning hardware, it only appends a local timestamp (preferably a monotonically increasing timestamp to ensure the alignment and consistency of multi-source data in the time dimension; this timestamp serves as the basis for subsequent combined positioning calculations, and its addition should be as close as possible to the data acquisition source to avoid time errors introduced by system scheduling delays), without parsing the data content, thus achieving transparent processing. This design not only preserves the integrity of the raw data but also facilitates the expansion and compatibility of subsequent protocols. Functionally, this module essentially constitutes a buffer and can be implemented as a character device or other standard device node, allowing the upper layer to access it through general system calls (such as read / write). In addition, for the location results generated by combined positioning, this module also provides a set of independently encapsulated dedicated input / output interfaces for receiving raw measurement data and combined positioning results from the upper layer, i.e., efficiently and isolatedly transmitting positioning information.

[0046] The second part includes a data encapsulation (processing) module and a combined positioning calculation module that run at the upper layer (such as the user space or service layer). The data encapsulation module is responsible for reading the raw measurement data packets with timestamps from the lower layer and processing and formatting the data according to the actual application requirements (such as parsing, fusion, and encapsulation). The data packaging and combined positioning calculation module executes multi-source fusion algorithms (such as GNSS / IMU / Wi-Fi fusion) based on the processed data to generate high-precision location results and writes the results back to the data processing module of the lower software layer for unified system use.

[0047] The third part is the system-level location service module. This module switches the data source of the operating system's native location service from the default positioning engine to the location output provided by the underlying data processing module. This seamlessly integrates the combined positioning results into the operating system's location service system, providing consistent and reliable location services to upper-layer applications. In this way, without modifying upper-layer applications, they can transparently use high-precision combined positioning data, achieving a system-level location service upgrade.

[0048] It should be noted that this solution does not depend on a specific operating system and has good cross-platform compatibility, making it applicable to various general-purpose or embedded operating system environments (such as Android, Linux, RTOS, and other platform environments).

[0049] An embodiment of the present invention also provides an electronic device, including a processor and a memory, the memory storing a computer program, wherein the processor executes the program to implement the combined positioning service framework.

[0050] An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned combined positioning service framework.

[0051] To better understand this invention, the data flow is illustrated below using a specific operational scenario: The GNSS receiver and IMU sensor onboard the vehicle generate raw observation data, which is captured by the underlying data processing module and appended with a precise monotonic clock timestamp before being stored in an input circular buffer. The upper-layer data packaging and combination positioning calculation module (currently loaded with a GNSS / IMU tightly coupled filtering plugin) reads the timestamped data via memory mapping, performs Kalman filtering calculations, and generates high-precision position, velocity, and attitude results. This result is written back to the output circular buffer managed by the underlying module. Simultaneously, the data source for the system location service module (such as Android LocationManager) is redirected to this output buffer. When the navigation application calls the standard location request interface, LocationManager directly obtains the fused high-precision location result from this buffer and returns it to the application; the entire process is transparent to the application.

[0052] The above embodiments of the present invention provide a combined positioning service framework, which aims to integrate high-precision and highly adaptable location sharing services into existing system location services in a manner that minimizes modification costs. It has the following significant advantages:

[0053] 1) By placing the integrated positioning algorithm module at the upper layer rather than the lower layer, it is not only convenient to replace and adjust the integrated positioning algorithm, but also to introduce different external data (such as road data) more flexibly, thereby improving the scalability and adaptability of the system.

[0054] 2) Compared to traditional front-end positioning methods, this solution performs better when GNSS signals are unavailable or of poor quality. Especially when using external data, it effectively improves the accuracy and reliability of the integrated positioning, meeting positioning needs in more complex scenarios.

[0055] 3) The overall solution is designed to minimize modifications to the existing system structure, reduce implementation difficulty and technical risks, thereby enabling the system to quickly and smoothly integrate new location service functions.

[0056] The specific data flow is as follows:

[0057] After collecting the combined positioning measurement data, it is first transmitted to the data processing module.

[0058] When the data processing module receives data, it appends a timestamp and puts the data packet into a buffer.

[0059] The data packaging module or the combined positioning module that directly supports the underlying data reads this timestamped data, encapsulates it as needed, and transmits it to the data packaging and combined positioning calculation module.

[0060] The data packaging and combination positioning calculation module generates accurate location data and sends it to the positioning data buffer.

[0061] Finally, the location service obtains the latest calculated location data from the location data processing module, completing the entire process.

[0062] In summary, this invention not only achieves effective processing and efficient output of combined positioning data, but also ensures the system's flexibility, reliability, and maintainability through optimized system architecture design, providing users with a more accurate and stable location service platform.

[0063] In the description of this specification, references to terms such as "embodiment," "example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0064] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A service framework for combined positioning, characterized in that, include: The underlying data processing module, configured at the operating system level, is used to receive raw measurement data from sensors or positioning hardware. Upon receiving the raw measurement data, it appends a local timestamp and caches the data without parsing the content of the raw measurement data. The data packaging and combined positioning calculation module, located in the upper application layer or service layer, is used to read the raw measurement data with timestamps from the underlying data processing module, execute the combined positioning algorithm to generate the location result, and write the location result back to the output buffer provided or managed by the underlying data processing module. The system location service module is configured to switch the data source to the output buffer of the underlying data processing module to obtain the location results generated by the data packaging and combination positioning calculation module, and to provide a unified location service to applications within the system.

2. The combined positioning service framework according to claim 1, characterized in that, The underlying data processing module is implemented through a character device or virtual device node, allowing the upper-layer module to perform read and write operations through standard system calls. The character device or virtual device node adopts a zero-copy or memory mapping mechanism, supporting concurrent access by multiple producers to a single consumer or multiple consumers.

3. The combined positioning service framework according to claim 2, characterized in that, The character device or virtual device node exposes standardized input / output instructions and ioctl control commands to combine the input and output of positioning data, read related settings, dynamically configure timestamp type, buffer size, data format version, and algorithm feedback parameters.

4. The combined positioning service framework according to claim 1, characterized in that, The local timestamp is a monotonically increasing timestamp generated based on the system's monotonic clock, used to ensure time alignment of multi-source sensor data.

5. The combined positioning service framework according to any one of claims 1-4, characterized in that, The underlying data processing module provides two sets of logically isolated, physically coexisting independent encapsulated interfaces: a raw measurement data input interface and a combined positioning result output interface, corresponding to independent circular buffers or memory-mapped areas, and distinguished by different file descriptors, ioctl control commands, or read / write direction semantics.

6. The combined positioning service framework according to claim 5, characterized in that, The combined positioning algorithm strategy includes one or more combinations of GNSS / IMU tightly coupled or loosely coupled filtering, Wi-Fi / Bluetooth fingerprint-assisted positioning, visual / laser odometry fusion, and high-precision map matching to enhance positioning.

7. The combined positioning service framework according to claim 6, characterized in that, The system location service module is a native location service component of the operating system. It redirects the data source to the output buffer of the underlying data processing module through configuration file overriding, service binding hijacking, HAL layer proxy, or runtime dynamic link library interception mechanisms.

8. The combined positioning service framework according to claim 5, characterized in that, The underlying data processing module adds timestamps by reducing intermediate modules to align the time of each data input source, ensuring that the sensor data is strictly aligned with the system clock.

9. The combined positioning service framework according to claim 7, characterized in that, The raw measurement data comes from one or more heterogeneous sensors, including GNSS, IMU, wheel speedometer, Wi-Fi, or Bluetooth.

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