Abstract: A system for estimating a location of a source transmitting a signal having a known modulation standard comprises a plurality of signal receiving circuits, each configured to receive the signal, to generate a denoised version of the signal, and to extract from the denoised version of the signal a set of signal parameters sufficient to at least partially reconstruct the denoised version of the signal. The system can also comprise a central processor circuit that receives the set of signal parameters from each signal receiving circuit and estimates the location of the source based on the signal parameters.

Abstract: A system for estimating a location of a source transmitting a spectral-diversity signal having a known form but at least one unknown parameter is disclosed. The system comprises signal receiving circuits, each receiving the spectral-diversity signal and computing, for each signal carrier component in the spectral-diversity signal, a cross-ambiguity function based on the known form and on the received spectral-diversity signal. A central processor circuit estimates the location of the source, by calculating an extremum of an objective function constructed from all the cross-ambiguity functions.

Abstract: There are provided a method of locating a transmitting source in multipath environment and system thereof. The method comprises: obtaining, by each receiver k of a plurality of spatially separated receivers, a sequence of samples of a signal received by the receiver, each sample respectively associated with a time of obtaining said sample, wherein one or more receivers m among the plurality of receivers k each obtain a respective sequence of samples over a plurality of different positions along a respective trajectory r(t) with respect to the site associated with the respective receiver m; and processing the obtained sequences of samples to identify the most likely location of the transmitting source. Optionally, most likely location can be estimated using a grid of potential locations within an area of interest.

Abstract: A system for estimating a location of a source transmitting a spectral-diversity signal having a known form but at least one unknown parameter is disclosed. The system comprises signal receiving circuits, each receiving the spectral-diversity signal and computing, for each signal carrier component in the spectral-diversity signal, a cross-ambiguity function based on the known form and on the received spectral-diversity signal. A central processor circuit estimates the location of the source, by calculating an extremum of an objective function constructed from all the cross-ambiguity functions.

Abstract: There are provided a method of locating a transmitting source in multipath environment and system thereof. The method comprises: obtaining, by each receiver k of a plurality of spatially separated receivers, a sequence of samples of a signal received by the receiver, each sample respectively associated with a time of obtaining said sample, wherein one or more receivers m among the plurality of receivers k each obtain a respective sequence of samples over a plurality of different positions along a respective trajectory r(t) with respect to the site associated with the respective receiver m; and processing the obtained sequences of samples to identify the most likely location of the transmitting source. Optionally, most likely location can be estimated using a grid of potential locations within an area of interest.

Abstract: An apparatus and method are disclosed for using specially designed landmarks to provide the position and orientation in three dimensions of an autonomous vehicle, such as a mobile robot. The landmarks are checkerboards of rectangular cells of contrasting colors that are arranged to create a pseudo-random pattern. The autonomous vehicle carries a recognition and measurement unit, for example including a camera and a digital computer that processes the output of the camera. A map stored in the recognition and measurement unit describes the position, orientation and dimensions of each pseudo-random checkerboard pattern. The recognition and measurement unit processes the image of a pseudo-random checkerboard pattern to identify the landmark on which the pattern is displayed and to calculate the position and orientation of the autonomous vehicle.