Iterative particle reduction methods and systems for localization and pattern recognition

A method for localization of a plurality of moveable nodes, comprising using a computing-based device to:

• establish a set of particles representing candidate positions for the plurality of moveable nodes;
• iteratively reduce the set of particles using one or more particle reduction iterations to provide a set of highest scoring particles, wherein each particle reduction iteration other than an initial particle reduction iteration eliminates at least some particles based on at least one constraint and a set of remaining particles from a prior iteration;
• model a movement of the plurality of moveable nodes by establishing a set of moving particles;
• iteratively reduce the set of moving particles using one or more moving particle reduction iterations to provide a final set of moving particles, wherein each moving particle reduction iteration other than an initial moving particle reduction iteration eliminates at least some moving particles based on at least one constraint and a set of remaining moving particles from a prior iteration;
• and
• after performing the plurality of moving particle reduction iterations, determine a set of probable locations of the plurality of moveable nodes based on the final set of moving particles.

A method comprising:

• using a plurality of sensors to provide a plurality of measured values;
• using the measured values to establish an initial set of particles representing candidate positions of the sensors;
• and
• iteratively eliminating those particles that do not satisfy a distance-based constraint, including testing each particle to see whether there are companion particles corresponding to other sensors at the appropriate distances, and eliminating those particles that do not have corresponding sets of companion particles at appropriate distances.