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In multi-spectral images made by Earth observation satellites that use push-broom scanning, such as those operated by Planet Labs Corp., moving objects can be identified by the appearance of the object at different locations in each spectral band. The apparent velocity can be measured if the relative acquisition time between images in different spectral bands is known to millisecond accuracy. The images in the Planet Labs archive are mosaics of individual exposures acquired at different times. Thus, there is not a unique acquisition time for each spectral band. In an earlier paper, we proposed a method to determine the relative acquisition times from the information in the images themselves. High-altitude balloons provide excellent targets to test our proposed method because of their high apparent velocity due to the orbital velocity of the satellite and geometric parallax in images aligned to the level of the ground. We use images of the Chinese balloon that crossed the US in February 2024 as well as images of an identical balloon over Colombia to test our method. Our proposed method appears to be successful and allows the measurement of the apparent velocity of moving objects from the information available in the archive. [ABSTRACT FROM AUTHOR]

Moving objects have characteristic signatures in multi-spectral images made by Earth observation satellites that use push broom scanning. While the general concept is applicable to all satellites of this type, each satellite design has its own unique imaging system and requires unique methods to analyze the characteristic signatures. We assess the feasibility of detecting moving objects and measuring their velocities in one particular archive of satellite images made by Planet Labs Corporation with their constellation of SuperDove satellites. Planet Labs data presents a particular challenge in that the images in the archive are mosaics of individual exposures and therefore do not have unique time stamps. We explain how the timing information can be restored indirectly. Our results indicate that the movement of common transportation vehicles, airplanes, cars, and boats, can be detected and measured. [ABSTRACT FROM AUTHOR]

Unidentified Aerial Phenomena (UAP) have resisted explanation and have received little formal scientific attention for 75 years. A primary objective of the Galileo Project is to build an integrated software and instrumentation system designed to conduct a multimodal census of aerial phenomena and to recognize anomalies. Here we present key motivations for the study of UAP and address historical objections to this research. We describe an approach for highlighting outlier events in the high-dimensional parameter space of our census measurements. We provide a detailed roadmap for deciding measurement requirements, as well as a science traceability matrix (STM) for connecting sought-after physical parameters to observables and instrument requirements. We also discuss potential strategies for deciding where to locate instruments for development, testing, and final deployment. Our instrument package is multimodal and multispectral, consisting of (1) wide-field cameras in multiple bands for targeting and tracking of aerial objects and deriving their positions and kinematics using triangulation; (2) narrow-field instruments including cameras for characterizing morphology, spectra, polarimetry, and photometry; (3) passive multistatic arrays of antennas and receivers for radar-derived range and kinematics; (4) radio spectrum analyzers to measure radio and microwave emissions; (5) microphones for sampling acoustic emissions in the infrasonic through ultrasonic frequency bands; and (6) environmental sensors for characterizing ambient conditions (temperature, pressure, humidity, and wind velocity), as well as quasistatic electric and magnetic fields, and energetic particles. The use of multispectral instruments and multiple sensor modalities will help to ensure that artifacts are recognized and that true detections are corroborated and verifiable. Data processing pipelines are being developed that apply state-of-the-art techniques for multi-sensor data fusion, hypothesis tracking, semi-supervised classification, and outlier detection. [ABSTRACT FROM AUTHOR]

The acoustic monitoring, omni-directional system (AMOS) in the Galileo Project is a passive, multi-band, field microphone suite designed to aid in the detection and characterization of aerial phenomena. Acoustic monitoring augments the Project's electromagnetic sensors suite by providing a relatively independent physical signal modality with which to validate the identification of known phenomena and to more fully characterize detected objects. The AMOS system spans infrasonic frequencies down to 0.05 Hz, all of audible, and ultrasonic frequencies up to 190 kHz. It uses three distinct systems with overlapping bandwidths: infrasonic (0.05 Hz – 20 Hz), audible (10 Hz – 20 kHz), and ultrasonic (16 kHz – 190 kHz). The sensors and their capture devices allow AMOS to monitor and characterize the tremendous range of sounds produced by natural and human-made aerial phenomena, and to encompass possible acoustic characteristics of novel sources. Sound signals from aerial objects can be captured and classified with a single microphone under the following conditions: the sound reaches the sensor; the sound level is above ambient noise; and the signal has not been excessively distorted by the transmission path. A preliminary examination of the signal and noise environment required for the detection and characterization of aerial objects, based on theoretical and empirical equations for sound attenuation in air, finds that moderately loud audible sources (100 dB) at 1 km are detectable, especially for frequencies below 1 kHz and in quiet, rural environments. Infrasonic sources are detectable at much longer distances and ultrasonic at much shorter distances. Preliminary aircraft recordings collected using the single, omni-directional audible microphone are presented, along with basic spectral analysis. Such data will be used in conjunction with flight transponder data to develop algorithms and corresponding software for quickly identifying known aircraft and characterizing the sound transmission path. Future work will include multi-sensor audible and infrasonic arrays for sound localization; analysis of larger and more diverse data sets; and exploration of machine learning and artificial intelligence integration for the detection and identification of many more types of known phenomena in all three frequency bands. [ABSTRACT FROM AUTHOR]

The Galileo Project aims to shed light on the nature and characteristics of Unidentified Aerial Phenomena (UAP). We are developing a multi-modal instrumentation suite that will monitor the sky in seven electromagnetic and three audio bands. Computing will play a critical role in this project, enabling the automated collection and processing of data. In this paper, we provide a brief overview of data sources, and describe our plan for computing infrastructure and architecture. We present a proposed real-time pipeline for distinguishing between natural and human-made phenomena, and for detecting objects that fall outside the phenomenological envelope of known phenomena. In addition, we outline the algorithms we will test and evaluate for use in offline data analysis. While preliminary, our work represents a significant step towards a unified data capture and analysis platform for the systematic detection and rigorous scientific study of unusual aerial phenomena in a regional airspace. [ABSTRACT FROM AUTHOR]

Quantitative three-dimensional (3D) position and velocity estimates obtained by passive radar will assist the Galileo Project in the detection and classification of aerial objects by providing critical measurements of range, location, and kinematics. These parameters will be combined with those derived from the Project's suite of electromagnetic sensors and used to separate known aerial objects from those exhibiting anomalous kinematics. SkyWatch, a passive multistatic radar system based on commercial broadcast FM radio transmitters of opportunity, is a network of receivers spaced at geographical scales that enables estimation of the 3D position and velocity time series of objects at altitudes up to 80 km, horizontal distances up to 150 km, and at velocities to ± 2 km/s (± 6 Mach). The receivers are designed to collect useful data in a variety of environments varying by terrain, transmitter power, relative transmitter distance, adjacent channel strength, etc. In some cases, the direct signal from the transmitter may be large enough to be used as the reference with which the echoes are correlated. In other cases, the direct signal may be weak or absent, in which case a reference is communicated to the receiver from another network node via the internet for echo correlation. Various techniques are discussed specific to the two modes of operation and a hybrid mode. Delay and Doppler data are sent via internet to a central server where triangulation is used to deduce time series of 3D positions and velocities. A multiple receiver (multistatic) radar experiment is undergoing Phase 1 testing, with several receivers placed at various distances around the Harvard–Smithsonian Center for Astrophysics (CfA), to validate full 3D position and velocity recovery. The experimental multistatic system intermittently records raw data for later processing to aid development. The results of the multistatic experiment will inform the design of a compact, economical receiver intended for deployment in a large-scale, mass-deployed mesh network. Such a network would greatly increase the probability of detecting and recording the movements of aerial objects with anomalous kinematics suggestive of Unidentified Aerial Phenomena (UAP). [ABSTRACT FROM AUTHOR]

In this paper, we review some of the extant literature on the study of interstellar objects (ISOs). With the forthcoming Vera C. Rubin Telescope and Legacy Survey of Space and Time (LSST), we find that 0. 3 8 − 8 4 'Oumuamua-like interstellar objects are expected to be detected in the next 10 years, with 95% confidence. The feasibility of a rendezvous trajectory has been demonstrated in previous work. In this paper, we investigate the requirements for a rendezvous mission with the primary objective of producing a resolved image of an interstellar object. We outline the rendezvous distances necessary as a function of resolution elements and object size. We expand upon current population synthesis models to account for the size dependency on the detection rates for reachable interstellar objects. We assess the trade-off between object diameter and occurrence rate, and conclude that objects with the size range between a third of the size and the size of 'Oumuamua will be optimal targets for an imaging rendezvous. We also discuss expectations for surface properties and spectral features of interstellar objects, as well as the benefits of various spacecraft storage locations. [ABSTRACT FROM AUTHOR]

To date, there are little reliable data on the position, velocity and acceleration characteristics of Unidentified Aerial Phenomena (UAP). The dual hardware and software system described in this document provides a means to address this gap. We describe a weatherized multi-camera system which can capture images in the visible, infrared and near infrared wavelengths. We then describe the software we will use to calibrate the cameras and to robustly localize objects-of-interest in three dimensions. We show how object localizations captured over time will be used to compute the velocity and acceleration of airborne objects. [ABSTRACT FROM AUTHOR]