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Hemiseer finds UAVs by using an array of antennas that passively watches the sky for reflected ambient RF signals. Both power and phase data are collected, processed through a unique metric that overlays both patterns. Antennas are grouped together into clusters, typically 4 antennas along with local small computers to get baseband RF signals onto a network and to a system where they are combined. A 3D location is sought as the source of an RF emitter, or reflector of ambient RF signals. Its energy and that of a common environmental background emitter reach all antennas. The phase, gain, and power of the emitter’s signal varies for each antenna due to distance and orientation of the antenna to the emitter location. Each antenna provides an observation at each frequency and time index. These observations include power and phase of incoming RF energy. Each observation is a summation of all local emitters and a background environment energy. The more antennas available at any moment, the better the quality of observation.
Conceptually, each observation from an antenna includes data from a large number of sources, such as all the leaves on a tree, each with its unique distance and power gain. We rely upon the large number of emitters in the environment to blur together into a single background signal. We consider each antenna to receive a uniform amount of background power with a phase that may vary by antenna. The problem then becomes one of finding the emitter location, emitter signal, and environmental background signal most consistent with the observations under the formulation:[5] Aobse(i obs)=Asrce(i (src+2D))4 DGr+AenvCenve(i env)Where:Aobs is the observed amplitude (W^0.5)θobs is the phase of the observation (rad)Aenv is the amplitude of the background environment signal common to all radios (W^0.5)Cenv is the power calibration factor of the receiver at the target frequencyθenv is the phase of the background environment signal that varies by radio (rad)Raw data from a radio source must be transformed to be maximally useful as an observation. Specifically, the raw data must be phase shifted and time shifted to account for both RF phase changes and baseband phase changes that occur as a signal reaches multiple antennas. The“observations” noted in this section are from shifting raw radio data to match arrival angle and timing for each 3D point being considered.
The Hemiseer solver uses a special formula to assess the difference between the observations and a proposed environmental power, emitter location, emitter power level, and emitter phase at each frequency of interest. It totals this difference across many frequencies, each contributing to the final solution accuracy. A truthful hypothesis of emitter location, emitter signal, and environment signal results in a perfect score – a zero residual, meaning there is no difference between observation and the proposed solution.Our solver scans the volume to be protected, solving for reflected energy at each point. Drones appear as local disruptions in the solver formula’s output. How “local” depends upon the frequency, antenna directivity, and sensor layout. For 4G, local ranges of 2-5 meters are typical. For 5G, ranges of 20-50 meters are projected, making for far fewer brief, but false, positive matches.
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5007 West Nassau Street
Tampa, FL 33607
