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ScanSAR Imaging
Published in Masanobu Shimada, Imaging from Spaceborne and Airborne SARs, Calibration, and Applications, 2018
As demonstrated previously, the AAP plays a very important role and must be calculated accurately. AAP can be obtained in one of two ways: (1) By measuring the history of power received by the ground-based receiver (Shimada et al. 2003) and converting the receiving time to the azimuth angle or (2) by estimating it using the SAR images of the Amazon Rainforest. Although the power history is intermittent, the first method provides a relatively easy means of obtaining AAP. However, its adaptation to the processor requires an accurate determination of the noise floor of the SAR system and processor. Uncertainty in estimating the noise floor may create another error source. In contrast, the second method always considers this noise floor.
THz Photonics
Published in Chi H. Lee, Microwave Photonics, 2017
Albert Redo-Sanchez, X.-C. Zhang
The noise floor comprises all noise sources and unwanted signals within a detection system. Some of the noises come from the sample and environment but others come from the device itself due to the electronics, contact resistance, wiring induction, thermal energy, etc. The most important electronic noise sources are the Johnson noise, the Shot noise, and the pink noise. The Johnson noise is generated by the collisions of the electrons with the lattice, and a typical value for a resistor of 1 kΩ and a bandwidth of 1 Hz is ~4 nV/Hz1/2. The Shot noise arises from the discrete nature of the electrons crossing a potential barrier. The fluctuation follows a Poisson distribution and the strength of this noise increases as the average current increases but often the SNR also increases, thus, the Shot noise is usually a problem at small currents. A typical value for a 1 Hz bandwidth and a current of 1 mA is ~0.5 nA/Hz1/2. The Pink noise is also known as 1/f noise or flicker noise, with a frequency spectrum such that the power spectral density is proportional to the reciprocal of the frequency.
Distributed Fiber-Optic Sensors and Their Applications
Published in Krzysztof Iniewski, Ginu Rajan, Krzysztof Iniewski, Optical Fiber Sensors, 2017
Balaji Srinivasan, Deepa Venkitesh
The receiver will be able to detect backscattered signals that are above the noise floor, that is, power level defined by the receiver sensitivity PD corresponding to signal-to-noise ratio (SNR) = 1. However, by employing SNR improvement (signal-to-noise-improvement ratio [SNIR]) techniques such as filtering or averaging or correlation, one can effectively lower the noise floor. Such reduction in the noise floor will allow us to interrogate a longer span of the optical fiber. The effective range of signals that could be detected is bounded by the highest level of Rayleigh backscattered power at the initial end of the fiber and the effective noise floor after signal processing. This range is known as the dynamic range of the OTDR. Note that the single-pass dynamic range (L) is half this value as we are dealing with the backscattered configuration.
Smart networks of autonomous in-situ soil sensors
Published in European Journal of Environmental and Civil Engineering, 2023
Xavier Chavanne, Jean-Pierre Frangi
Signal strength is assessed at the gateway for each received point owing to two indicators. The Received Signal Strength Indication (RSSI) is the absolute signal power measured in dBm. It is a negative value with a minimum of −120 dBm. Signal-to-Noise Ratio (SNR) is the ratio in dB between the signal power and the noise floor power level, which represents all unwanted interfering signal sources. LoRa can work below the noise floor, with SNR values as low as −24 dB. SNR is compared to the rate of losses we determine over time i the following section.