Fingerprint-based Bluetooth Localization (Fingerprint-based Bluetooth Localization) is a commonly used indoor positioning algorithm. Its basic principle is to establish a fingerprint database by recording the Bluetooth signal strength values at different locations, and then according to the Bluetooth signal strength values received by the device, Match the most similar fingerprints to determine where the device is located.

The working principle of the fingerprint algorithm is: first, collect and record the Bluetooth signal strength at different locations in the environment, and establish a corresponding signal strength database. Then, during actual use, when the device receives a Bluetooth signal, it will be compared with the previously recorded signal strength database to determine the current location of the device.
Specifically, in Bluetooth positioning, the fingerprint algorithm can be performed through the following steps:

  1. Signal acquisition
    In the area that needs to be positioned, use the Bluetooth locator to collect the Bluetooth signals at each location, and record the signal name, strength value and other information. Usually collect multiple signal strength values at multiple locations as a fingerprint library

  2. Fingerprint modeling
    Through machine learning and other methods, the collected signal strength values are converted into location fingerprints, that is, multiple signal strength values at each location are composed into a vector, and stored in the fingerprint database to form a mapping relationship between location and fingerprint.

  3. Position calculation
    When the device receives a Bluetooth signal, it compares it with the fingerprints in the fingerprint library and finds the most similar fingerprint position to determine the location of the device. Machine learning and statistical methods are usually used, such as KNN, Bayesian classification, etc., to perform positioning calculations based on the positions of multiple most similar fingerprints, and output the actual position coordinates.

Fingerprint algorithm Bluetooth positioning has the following advantages:

It can accurately identify the room or location where the device is located, and achieve high-precision indoor positioning.

By establishing a signal strength database and dynamically updating it, it can adapt to changing signals in different environments and improve the robustness and stability of positioning.

Combined with other sensor data, such as accelerometers, gyroscopes, etc., the positioning accuracy and reliability can be further improved.