Biblio

A new approach to micro-Doppler signal analysis is presented in this article. Novel chirp rate estimators in the time-frequency domain were used for this purpose, which provided the chirp rate of micro-Doppler signatures, allowing the classification of objects in the urban environment. As an example verifying the method, a signal from a high-resolution radar with a linear frequency modulated continuous wave (FMCW) recording an echo reflected from a pedestrian was used to validate the proposed algorithms for chirp rate estimation. The obtained results are plotted on saturated accelerograms, giving an additional parameter dedicated for target classification in security systems utilizing radar sensors for target detection.

One of the primary motivations for using ultrasound reflectometry for fingerprint imaging is the promise of increased spoof resistance over conventional optical or capacitive sensing approaches due to the ability for ultrasound to determine the elastic impedance of the imaged material. A fake 3D printed plastic finger can therefore be easily distinguished from a real finger. However, ultrasonic sensors are still vulnerable to materials that are similar in impedance to tissue, such as water or rubber. Previously we demonstrated an ultrasonic fingerprint reader operating with 1.3GHz ultrasound based on pulse echo impedance imaging on the backside silicon interface. In this work, we utilize the large bandwidth of these sensors to differentiate between a finger and materials with similar impedances using the frequency response of elastic impedance obtained by transducer excitation with a wideband RF chirp signal. The reflected signal is a strong function of impedance mismatch and absorption [Hoople 2015].

In multicarrier direct modulation direct detection systems, interaction between laser chirp and fiber group velocity dispersion induces subcarrier-to-subcarrier intermixing interferences (SSII) after detection. Such SSII become a major impairment in orthogonal frequency division multiplexing-based access systems, where a high modulation index, leading to large chirp, is required to maximize the system power budget. In this letter, we present and experimentally verify an analytical formulation to predict the level of signal and SSII and estimate the signal to noise ratio of each subcarrier, enabling improved bit-and-power loading and subcarrier attribution. The reported model is compact, and only requires the knowledge of basic link characteristics and laser parameters that can easily be measured.