Adam Cegła’s Post

https://lnkd.in/gGxSYxjX My latest paper and a new paper on extremely red quasars. Used adaptive optics integral field spectroscopy. Found the [OIII] emissions are more spatially compact than normal quasars. #Astronomy #Quasars #Galaxies

Magnetic Sensitivity of #FOG #IMU full text: https://lnkd.in/gAWqCEec Inertial measurement unit (IMU) is the key of position and attitude system to obtain high-precision position and attitude information and realize high-precision airborne Earth observation. IMU with high-precision fiber optic gyro (FOG IMU) is sensitive to magnetic field due to Faraday effect of fiber coil, and the performance parameters of FOG zero bias and drift are deteriorated, thus the performance of IMU decreases. For FOG without taking any measures, its zero bias sensitivity is 104 (°)/(h·T), which can meet the requirements of general low-precision inertial measurement systems, but typical high-precision inertial navigation systems (such as POS) require FOG zero bias sensitivity of 1 ~ 10 (°)/(h·T), because of this, To achieve high precision IMU with FOG, some technical measures must be taken to reduce the magnetic sensitivity of FOG. 1. Methods to reduce magnetic sensitivity In the development stage of FOG, the technical measures to reduce magnetic sensitivity are mainly depolarization technology and advanced loop winding technology. Single-mode fiber can achieve lower magnetic field sensitivity than the polarization-preserving FOG through depolarization technology. The polarization-preserving gyro can suppress zero drift well because of its large linear bifold beam relative to the circular bifold beam induced by magnetic field. However, the main axis of polarization-preserving optical fiber has slow rotation in the drawing process, and it will also lead to torsion when winding optical fiber coil. Therefore, the Faraday effect in polarization-maintaining fiber is not completely zero. Using advanced winding technology to reduce the residual torsion of the coil and effectively control the tensioning force during the winding process, it can improve the quality of the polarity-maintaining coil and reduce the magnetic sensitivity. In addition, multiple compensators can be configured in the FOG scheme, the combined magnetic sensitivity of the compensators can be used to eliminate the magnetic sensitivity of the coil, and the FOG magnetic sensitivity can be reduced by using a new type of optical fiber with less magnetic sensitivity.

Magnetic Sensitivity of #FOG #IMU full text: https://lnkd.in/gKiDn8zu Inertial measurement unit (IMU) is the key of position and attitude system to obtain high-precision position and attitude information and realize high-precision airborne Earth observation. IMU with high-precision fiber optic gyro (FOG IMU) is sensitive to magnetic field due to Faraday effect of fiber coil, and the performance parameters of FOG zero bias and drift are deteriorated, thus the performance of IMU decreases. For FOG without taking any measures, its zero bias sensitivity is 104 (°)/(h·T), which can meet the requirements of general low-precision inertial measurement systems, but typical high-precision inertial navigation systems (such as POS) require FOG zero bias sensitivity of 1 ~ 10 (°)/(h·T), because of this, To achieve high precision IMU with FOG, some technical measures must be taken to reduce the magnetic sensitivity of FOG. 1. Methods to reduce magnetic sensitivity In the development stage of FOG, the technical measures to reduce magnetic sensitivity are mainly depolarization technology and advanced loop winding technology. Single-mode fiber can achieve lower magnetic field sensitivity than the polarization-preserving FOG through depolarization technology. The polarization-preserving gyro can suppress zero drift well because of its large linear bifold beam relative to the circular bifold beam induced by magnetic field. However, the main axis of polarization-preserving optical fiber has slow rotation in the drawing process, and it will also lead to torsion when winding optical fiber coil. Therefore, the Faraday effect in polarization-maintaining fiber is not completely zero. Using advanced winding technology to reduce the residual torsion of the coil and effectively control the tensioning force during the winding process, it can improve the quality of the polarity-maintaining coil and reduce the magnetic sensitivity. In addition, multiple compensators can be configured in the FOG scheme, the combined magnetic sensitivity of the compensators can be used to eliminate the magnetic sensitivity of the coil, and the FOG magnetic sensitivity can be reduced by using a new type of optical fiber with less magnetic sensitivity.

🌍 Dreaming of high-res views of Earth? A PIC-powered device is the answer! The global picture doesn’t get much bigger than Earth observation #SatelliteImagery. Especially as weather conditions become more antagonistic to orthodox methods, new #SatelliteTechnology is crucial for detailed imaging. To that end, we are very proud of our work on the development of the first-ever photonic-assisted receiver module for scan-on-receive #SCORE synthetic aperture radar #SAR, a milestone for the SPACEBEAM Project. Soon, weather conditions and time constraints won't hinder Earth observation from Space, all thanks to #IntegratedPhotonics. 🛰️ 🔴This #photonic device delivers unparalleled #beamsteering precision, handling signals from a 12-element antenna array and synthesizing multiple beams simultaneously, all while consuming just three and a half watts! ➡️How it was designed is a perfect example of the vertically-integrated solutions development done at LioniX. Taking a satellite imaging technique and implementing it on hybrid PIC device the size of a euro coin 🪙 using both TriPleX® silicon nitride and indium phosphide, is about as complicated as it sounds. Unless you have Ahmad Mohammad explaining it to you, then it’s as easy as a Sunday morning. Read his explainer blog article here: https://lnkd.in/eQ_cXerQ

Some remarks related to the Radar remote sensing: -Radar Remote Sensing: Utilizes electromagnetic energy backscattered from ground targets to extract information about their physical and dielectric properties. -Advantages of Radar Imaging: Capable of all-hour and all-weather imaging. Transmits microwave pulses with a predefined pulse repetition frequency, depending on the platform. Backscatter Dependence: Intensity and phase of backscattered energy are influenced by surface roughness and moisture content of the ground target. -Radar Antenna Function: Receives backscattered energy from ground targets subjected to transmitted microwave pulses. -Side-Looking Aperture Radar: Features side-looking imaging geometry (range direction) with forward motion capability (azimuth direction). -Synthetic Aperture Radar (SAR): Developed to reduce the antenna size of radar satellites by using multiple looks on the same ground target. SAR geometry involves different angles and parameters 

Hi, GNSS community, I am excited to share that an article related to Sagnac effects in GNSS has been published in the Journal of Geodesy. Thanks for Prof. Jay Farrell’s collaboration.   The Sagnac correction accounts for Earth's rotation during signal travel, avoiding the need to compute accurate signal travel time to apply to the rotation matrix. This correction is widely referenced in GNSS textbooks and implemented in many systems. Three years ago, when we explored this method, we were surprised to find that the derivation of the Sagnac correction proposed around 2000 is only valid for stationary receivers. More importantly, there was no analysis of the error incurred when using this approximate method. This work has proved that the Sagnac correction introduces a range error of less than 1 mm for most GNSS orbits. Wanna skip the dense mathematical derivations? please see Section 6 which summarizes the error bounds for various orbital radii.

🚀 Did you know what a cycle slip is and its consequences in GNSS? A cycle slip is a discontinuity in the phase of a signal. This occurs when the receiver temporarily loses phase tracking, and upon reacquiring it, there is a jump in the cycle count that is not computed correctly. Where does it occur most frequently? 🌲In challenging environments, where the signal struggles to reach the receiver, such as dense forests or urban areas with tall buildings. 🌞Due to high ionospheric gradients, which can cause drastic changes in the signal, increasing the probability of a cycle slip.   Why is it critical to correct them? Measurements affected by cycle slips must be removed or corrected before entering the positioning engine. A cycle slip may introduce an error equal to the wavelength multiplied by the number of skipped cycles.   In GNSS, the typical wavelength is around 20 cm (depending on frequency), meaning the error can range from a few centimeters to several meters in extreme cases.   How are cycle slips detected? 1️⃣Single-frequency methods: Code Minus Carrier (CMC): This technique calculates the difference between the code and carrier phase. While useful, it can only detect large cycle slips, as small slips (1–2 cycles) are masked by noise, given that the order of magnitude of the noise is measured in meters.   2️⃣Dual-frequency methods: Melbourne-Wübbena: This method combines the wide-lane of the phase and narrow-lane of the code, removing ionospheric delay, amplifying the jumps (due to increased wavelength), and reducing noise in the narrow lane. This makes it easier to detect smaller cycle slips.   Polynomial fit + Geometry-Free Combination: This algorithm fits a polynomial with previous measurements and detects a cycle slip if the new measurement deviates beyond a defined threshold.   Obviously these algorithms are not perfect on their own. The key is to implement as many barriers as possible and tune them effectively to avoid false alarms. In the following example, after applying Polynomial fit + Geometry-Free Combination and compute VTEC (Vertical Total Electron Content) it can be seen that a cycle slip was not detected on 8 hour. What algorithms for cycle slip detection do you know? #CycleSlip #GNSS #SignalProcessing #SatelliteTechnology #SpaceInnovation #GNSSAlgorithms #NavigationSystems #IonosphericEffects

Under ground, under water, and where satellite signals are often blocked — a new 'quantum compass' proof of concept could provide accurate geolocation data where GPS can't reach. 🧭 The quantum compass, which could be ready for widespread use in just a few years, employs an advanced accelerometer that can cross reference observed movement through space, against a known starting point, and from there, pinpoint the relative current and future spatial location.

We are pleased to announce that a new #journal article written by our very own Dennis Langer is now available online, to be published in the IEEE Transactions on Geoscience and Remote Sensing. Several unique and repeatable satellite maneuvers for extending satellite imaging capabilities are presented in it. They are demonstrated with Norwegian University of Science and Technology (NTNU)'s HYPSO-1, a 6U satellite with a hyperspectral imager. The maneuvers include: - Simultaneous pointing and imaging to track geographic features such as rivers - Pointing and on-board classification to downlink information about a target in Norway less than 2 minutes after imaging - Slewing to increase the signal-to-noise ratio over dark targets Check out the early access article at IEEE Xplore: https://lnkd.in/d243Th8z! #cubesats #remotesensing #satops #EO

Seeing the Vibration from Fiber-Optic Cables: Rain Intensity Monitoring using Deep Frequency Filtering Publication Date: 6/17/2024 Event: #CVPR2024 Workshop: 20th Workshop on Perception Beyond the Visible Spectrum Reference: pp. 3017-3026, 2024 Authors: Zhuocheng Jiang, NEC Laboratories America, Inc.; Yangmin (Benjamin) D., NEC Laboratories America, Inc.; Junhui Zhao NEC, Eversource Energy; Yue Tian, NEC Laboratories America, Inc.; Shaobo Han, NEC Laboratories America, Inc.; Sarper Ozharar, NEC Laboratories America, Inc.; Ting Wang, NEC Laboratories America, Inc.; James M. Moore, Verizon Abstract: The various sensing technologies such as cameras #LiDAR radar and satellites with advanced machine learning models offers a comprehensive approach to environmental perception and understanding. This paper introduces an innovative Distributed Fiber Optic Sensing (DFOS) technology utilizing the existing telecommunication infrastructure networks for rain intensity monitoring. DFOS enables a novel way to monitor weather condition and environmental changes provides real-time continuous and precise measurements over large areas and delivers comprehensive insights beyond the visible spectrum. We use rain intensity as an example to demonstrate the sensing capabilities of DFOS system. To enhance the rain sensing performance we introduce a Deep Phase-Magnitude Network (DFMN) divide the raw sensing data into phase and magnitude component allowing targeted feature learning on each component independently. Furthermore we propose a Phase Frequency learnable filter (PFLF) for the phase component filtering and conduct standard convolution layers on the magnitude component leveraging the inherent physical properties of optical fiber sensing. We formulate the phase-magnitude channel into a parallel network and subsequently fuse the features for a comprehensive analysis in the end. Experimental results on the collected fiber sensing data show that the proposed method performs favorably against the state-of-the-art approaches. Learn more: https://lnkd.in/ey8uV7BP