NH UAP Report

MULTI-SENSOR CORRELATION

PROJECT

PROPERTY OWNER

DR. JIM SEGALA

DR. GARRY NOLAN

PROJECT OVERVIEW

• Objective: Capture correlated multi-sensor data of anomalous events on target property

• Sensor Data Types: Environmental Data, Network, Acceleration, Magnetometer, Gyroscopic, GPS, Microwave, Gamma, Sound Energy, IR/EO/UV video

• History: Recent multi-sensor data acquisitions indicate high probability of true anomalous events

• Next Steps: Project Team requests additional funding to improve sensor package and refine measurements to:

• Determine object geolocation

• Calculate signal field strength to better define anomalous object characteristics

BACKGROUND

• Anomalous events began in Nov, 2021 and have continued at high frequency

• Orb sightings

• Camera / video data corruption

• Several “poltergeist” events

• Personnel who are familiar with and have expressed interest in the property:

• Jim Semivan, Dr. John Alexander, Jay Stratton, Dr. Travis Taylor, Dr. Garry Nolan, David Grusch, Lue Elizondo, David Fravor, Dr. Jim Segala

• Trail camera, iPhone, and digital camera videos have been captured continuously since November 2021

• Detailed ADSB assessment performed on videos confirms objects are not aircraft

EXAMPLE DATA CAPTURE USING BASIC MUPAS SENSOR

• Event captured on 3/11/24 on target property

• Trail camera video captured during this time shows numerous anomalous flashing lights in the tree line

• Anomalous activity most frequent during peak Gamma and Microwave signals

Four Independent Sensor Channels + Trail Camera All Captured Simultaneous Anomalous Data!

Anomalous light in tree line

PROJECT CONCEPT

• Project team requests funding to thoroughly instrument property with multiple sensors

• Multiple sensors will enable geolocation calculation of anomalous object

• Correlated multi-sensor data will provide robust statistical evidence for likelihood of anomalous event and help ascertain nature of anomalous object

• Notes:

• All wiring to the sensor packs (power and Ethernet) will be underground

• All collected data transferred to cloud over Internet connection

Concept

• Mount 5 MUPAS sensors on poles around property

• Utilize Time Difference of Arrival techniques to Geolocate anomalous activity

• Correlate sensor and video data to validate object geolocation and parametrics required to produce sensor readings

DESCRIPTION OF SENSOR PACKS

• Sensors housed in watertight enclosure yet allowing for signal transparency.

• Multiple sensor packs connected on high-speed mesh network allowing triangulation of signals and objects.

• Sensor readings taken in three dimensions simultaneously (microwave, magnetic, sound, gyroscopic).

• Microwave and gamma ray spectrum recordings.

• Visible and infrared video recordings with AI based tracking capability.

• Local caching of sensor and video data in disconnected mode.

DATA COLLECTION DICTIONARY

• Gravitation Field Sensor

• Gravitational field fluctuations have been known to occur while strange phenomena are being observed.

• Potentially due to the phenomenon creating local changes to the space-time metric? Other reasons?

• Acceleration and Gyroscopic Sensors

• If orbs produce alter gravity (i.e., the local space-time metric), this can be measured locally using accelerometers.

• Magnetic and Electric Field Sensors

• Small changes in the magnetic and electric field vectors indicate the presence of an external changing electromagnetic field in the vicinity of the sensors.

• Observations of orbs have been previously correlated with detectable changes in local electromagnetic fields.

• Gamma Ray Detector

• As orbs travel do they generate gamma-ray particles? Alleged orb presence seems to be correlated with gamma-ray particle production.

• GPS

• The GPS in the MUPAS device connects to several satellites to obtain accurate positioning. A secondary effect of strange phenomenon may be an interruption in satellite communications.

• Temperature/Pressure/Humidity

• Sudden changes in the environmental readings indicate a slight change in room temperature, barometric pressure, or relative humidity could indicate the presence of a primary signal.

• Sound Energy

• Do changes in local environmental signals produce acoustic waves as energetic orbs travel past sensors?

• Visual, Infrared, and Ultraviolet Video

• Do the observed orbs emit or reflect light across the electromagnetic spectrum? Monitoring the most extensive spectrum possible provides the best possible sensor data.