Supplier eBooks

49 | Geolocation, Navigation, and Timing Geolocation services are one of the most used wireless services around the globe for applications such as personal travel, transportation, aviation, and surveying. The most common method of geolocation is using Global Navigation Satellite Systems (GNSS), such as Galileo (European Union), GPS (USA), GLONASS (Russia), QZSS (Japan), IRNSS (India), and BeiDou (China). These systems use satellite networks in the Earth's orbit that constantly transmit ranging and timing data accessible by GNSS- enabled receivers. These receivers are also equipped with circuits that can compare the timing and ranging data from several satellites to compute the exact position of the GNSS receiver relative to the satellite constellation. By storing and comparing multiple GNSS receiver measurements, it is possible to estimate the direction and velocity of travel. Radar Radar is an older RF use case that continues to evolve and be implemented in new ways. It uses the dynamics of RF signal reflections (known as backscatter) from a radar transmitter to gather information about the environment and targets. Readings from tracking radar can decipher information about a radar target, such as its size, direction, velocity, and other characteristics. Many other types of radar, such as weather radar and synthetic aperture radar (SAR), are used to map and capture information precisely about the composition of target land surfaces (Figure 2). To achieve these readings, the radar must be able to measure the difference in time between when a radar signal is transmitted and when the backscatter signals are received. This measurement is derived from the following formula: In this formula, R is the slant range from the antenna to the target, c 0 is the speed of light, and t is the measured run-time. Information about the surface that caused the radar reflections can be determined based on more advanced signal characteristics. Using studies of how RF signals interact with different materials, one can determine the condition of the objects being illuminated by a radar with the appropriate technology. For instance, a weather radar can be used to determine the amount of water vapor density in the clouds, and radar used in grain silos can determine the depth of the grain as well as the moisture content. AI and machine learning (ML) technologies make it possible to infer even more information from radar targets. Researchers are using these tools for space exploration to map distant celestial bodies and discover ancient human occupation sites and buildings previously hidden by dense foliage or complex landscape features. RF-Based Imaging and Sensing Beyond radar, RF signals can also be used similarly to visual and IR for imaging. Because RF signals interact with visual and IR light differently than with physical objects, RF imaging technologies can be used for unique use cases. RF imaging technologies also use different methods of capturing electromagnetic energy than typical cameras do, using compact antenna array designs instead of photocapture cells. Depending on the frequency at which the RF imager operates, the RF signals captured may more efficiently Figure 2: An SAR image of Sotra Facula on Titan. (Source: NASA) 2

• Cover