An algorithm enables localization of humans and robots in areas where GPS is unavailable. The Army needs to be able to localize agents operating in physically complex, unknown, and infrastructure-poor environments. This capability is critical to help find dismounted soldiers and for humans and robotic agents to team together effectively.

Obstacles inside a building, especially when their size is much larger than the wavelength of the wireless signal, weaken the power of the signal (attenuation) and redirect its flow (called multipath), making a wireless signal very unreliable for communicating information about location.

Typical approaches to localization, which use a wireless signal’s power or delay (i.e., how long it takes to reach a target from a source), work well in outdoor scenes with minimal obstacles; however, they perform poorly in obstacle-rich scenes. The new technique determines the direction of arrival (DoA) of a radio frequency signal source, which is a fundamental enabler of localization.

The technique is robust to multiple scattering effects, unlike existing methods such as those that rely on the phase or time of arrival of the signal to estimate the DoA. This means that even in the presence of occluders that scatter the signal in different directions before it is received by the receiver, the proposed approach can accurately estimate the direction of the source. The underlying idea is that the gradient of the spatially sampled received signal strength (RSS) carries information about the source direction. The algorithm statistically models the RSS gradient and controls for spatial outliers and correlations.

Importantly, when the signal is extremely noisy, the estimator correctly outputs that no DoA is present, rather than incorrectly estimating an arbitrary direction. The output is an estimated DoA and associated uncertainty.

The approach was validated with several publicly available as well as in-house collected measurement datasets at 40 MHz and 2.4G Hz bands, as well as data from high-fidelity simulations. The technique works in conditions of heavy multipath in which classical phase or time-of-arrival-based estimates would fail.

In addition to not requiring any fixed infrastructure, the technique also does not rely on any prior training data, knowledge about the environment, multiple antennas, or prior calibration between nodes.

For more information, contact the ARL Public Affairs Office at 301-394-3590.

Tech Briefs Magazine

This article first appeared in the October, 2019 issue of Tech Briefs Magazine.

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