- Multi-channel Signal Processing
- Sensor and Relay Networks
- Multi-antenna and Multi-channel Signal Processing for Communications
- Applications of Sensor Array and Multi-channel Signal Processing
- Adaptive Array Signal Processing
- Sensor Array Processing
In this paper, the localization of an emitter based on Time Difference of Arrival (TDoA) has been investigated. The classical least-squares (LS) algorithm, with a limited number of TDoA measurements, has been utilized for obtaining a closed-form solution to the source localization problem. Recently, an extension of the classical LS algorithm has been employed in an attempt to improve the precision of the localization technique by using a larger set of TDoA estimates.
Moving platforms enable sparse arrays to assume higher degrees of freedom and lead to increased number of lags. In essence, array motion can fill the holes in the spatial autocorrelation lags associated with a fixed platform and, therefore, increase the number of sources detectable by the same number of physical array sensors. In this paper, we consider coprime arrays, and assume quasi-stationarity of the environment, where the source locations and waveforms are considered invariant over array motion of half wavelength.
In the 3.5 GHz Citizens Broadband Radio Service (CBRS), 100 MHz of spectrum will be shared between commercial users and federal incumbents. Dynamic use of the band relies on a network of sensors dedicated to detecting the presence of federal incumbent signals and triggering protection mechanisms when necessary. This paper uses field-measured waveforms of incumbent signals in and adjacent to the band to evaluate the performance of matched-filter detectors for these sensors.