DSP uses digital signal processing to convert and analyze signals such as audio, video, voice, light, temperature, pressure or position, and then output usable data
Analog converter takes this real-world information (such as light or sound waves) and turns it into a digital format (binary code); then, DSP technology processes this code and feeds the digitized information back out; this process is performed very quickly
DSP is used in many electronic applications
A computer may use DSP to monitor security, transmit telephone calls, compress video or play a movie on a home theater system
In certain applications, the quality of the signal is enhanced to provide even more information and detail than what humans are able to sense – for example, a computer enhancing medical images
Analog signal processing is also possible, but the process is made much faster and more efficient with digital signal processing – improves speed and accuracy
I’ve talked before about how a sensor hub can be used to offload the work of sensor fusion from the main CPU of your device, and a DSP offers the same benefit, allowing you to run multiple functions without overtaxing your primary CPU
In sensing applications, sensors are gathering information on light, sound, or, if it’s a motion sensor, 3D movement and relative location; in AR/VR this might mean tracking hand motions; in robotics, this means mapping out surrounding objects and relaying that data to avoid crashes
Some multi-axis sensors, like IMUs, do their own data processing via sensor fusion to blend several inputs, such as from a gyroscope and an accelerometer. A DSP can then process inputs (signals) from multiple sensors of different types, and this could include contextual motion data that’s already been processed via sensor fusion and is now being added to additional sensor data (such as light, sound, etc.) to tell a comprehensive story
Always-on functions operate in the background, and can be a combination of multiple sensor types, such as IMU/Voice/other (e.g. presence detection) for more comprehensive context
Embedded DSPs can handle all of these always-on functions in real-time, which is critical to performance without slowing down the CPU or draining its battery – offers a more cost-effective, low-power solution.
Example always-on functions: pedometers, GPS, lane assist or passenger detection in cars, voice control on TV remotes
Most smart audio and video/imaging applications require at least some of these types of always-on voice control and object detection functions
On a DSP, these computations can be run in parallel with the CPU, so that many different functions can be carried out at the same time
More flexible hardware interpretation
Easier to be used across a variety of devices because the encoding and decoding techniques are standard
Encryption and compression help with security as well as efficient transmission and downloading
Analog signals were used traditionally for long distances, but are prone to distortion, interference and even security breaches
Along with higher speed and accuracy, digital signal processing offers a number of benefits, including:
By running a small always-on DSP, you can enable functions in the background: