Conclusion Radar sensing technology can provide highly accurate measurements for distance and motion applications. However, it can consume a lot of power to achieve accuracy, and it typically involves a complex design process. By implementing PCR, the Acconeer A111 integrated radar sensor provides the combination of high accuracy and low power consumption required for smart products and other emerging applications. The companion software development kit (SDK) abstracts the complexity of radar signal processing, providing the kind of higher level data required at the application level. Using the SDK with an A111-based development board, engineers can rapidly gain experience in radar sensing technology and quickly implement sophisticated applications able to discern objects and track movement with millimeter resolution.
Listing 1: This snippet from a sample application in the Analog Devices 3D ToF SDK distribution demonstrates the few steps required to acquire depth and IR images and classify them with an inference model. (Code source: Analog Devices)
for initialization, RSS activation, configuration creation, and service instantiation. For example, to use the Envelope Service, developers would call acc_service_envelope_ configuration_create() to create the necessary configuration and use that configuration as a parameter in calling acc_service_create() to instantiate a service object. By exploring the C-language sample code, developers can quickly gain experience using the RSS API to build specialized radar applications with custom detectors. To help developers more rapidly gain familiarity with radar-based sensing in general and RSS services in particular,
Acconeer also provides sample code in its Python Exploration Kit software repository. Designed to work with the Acconeer SDK and evaluation kits such as the XM112, the Python Exploration Kit helps developers take advantage of Python’s productivity advantages for working with RSS services and detectors. Along with basic examples, the kit provides sample code for implementing very sophisticated measurement applications including detecting breathing patterns in sleeping subjects, using phase information to track relative movements, detecting approaching obstacles, and more.
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