New Method for Helicopter Noise Mapping
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Noise Tutorial Part IV ~ Noise Factor
Noise Tutorial Part IV ~ Noise Factor Whitham D. Reeve Anchorage, Alaska USA See last page for document information Noise Tutorial IV ~ Noise Factor Abstract: With the exception of some solar radio bursts, the extraterrestrial emissions received on Earth’s surface are very weak. Noise places a limit on the minimum detection capabilities of a radio telescope and may mask or corrupt these weak emissions. An understanding of noise and its measurement will help observers minimize its effects. This paper is a tutorial and includes six parts. Table of Contents Page Part I ~ Noise Concepts 1-1 Introduction 1-2 Basic noise sources 1-3 Noise amplitude 1-4 References Part II ~ Additional Noise Concepts 2-1 Noise spectrum 2-2 Noise bandwidth 2-3 Noise temperature 2-4 Noise power 2-5 Combinations of noisy resistors 2-6 References Part III ~ Attenuator and Amplifier Noise 3-1 Attenuation effects on noise temperature 3-2 Amplifier noise 3-3 Cascaded amplifiers 3-4 References Part IV ~ Noise Factor 4-1 Noise factor and noise figure 4-1 4-2 Noise factor of cascaded devices 4-7 4-3 References 4-11 Part V ~ Noise Measurements Concepts 5-1 General considerations for noise factor measurements 5-2 Noise factor measurements with the Y-factor method 5-3 References Part VI ~ Noise Measurements with a Spectrum Analyzer 6-1 Noise factor measurements with a spectrum analyzer 6-2 References See last page for document information Noise Tutorial IV ~ Noise Factor Part IV ~ Noise Factor 4-1. Noise factor and noise figure Noise factor and noise figure indicates the noisiness of a radio frequency device by comparing it to a reference noise source. -
Next Topic: NOISE
ECE145A/ECE218A Performance Limitations of Amplifiers 1. Distortion in Nonlinear Systems The upper limit of useful operation is limited by distortion. All analog systems and components of systems (amplifiers and mixers for example) become nonlinear when driven at large signal levels. The nonlinearity distorts the desired signal. This distortion exhibits itself in several ways: 1. Gain compression or expansion (sometimes called AM – AM distortion) 2. Phase distortion (sometimes called AM – PM distortion) 3. Unwanted frequencies (spurious outputs or spurs) in the output spectrum. For a single input, this appears at harmonic frequencies, creating harmonic distortion or HD. With multiple input signals, in-band distortion is created, called intermodulation distortion or IMD. When these spurs interfere with the desired signal, the S/N ratio or SINAD (Signal to noise plus distortion ratio) is degraded. Gain Compression. The nonlinear transfer characteristic of the component shows up in the grossest sense when the gain is no longer constant with input power. That is, if Pout is no longer linearly related to Pin, then the device is clearly nonlinear and distortion can be expected. Pout Pin P1dB, the input power required to compress the gain by 1 dB, is often used as a simple to measure index of gain compression. An amplifier with 1 dB of gain compression will generate severe distortion. Distortion generation in amplifiers can be understood by modeling the amplifier’s transfer characteristic with a simple power series function: 3 VaVaVout=−13 in in Of course, in a real amplifier, there may be terms of all orders present, but this simple cubic nonlinearity is easy to visualize. -
Fast, High Quality Noise
The Importance of Being Noisy: Fast, High Quality Noise Natalya Tatarchuk 3D Application Research Group AMD Graphics Products Group Outline Introduction: procedural techniques and noise Properties of ideal noise primitive Lattice Noise Types Noise Summation Techniques Reducing artifacts General strategies Antialiasing Snow accumulation and terrain generation Conclusion Outline Introduction: procedural techniques and noise Properties of ideal noise primitive Noise in real-time using Direct3D API Lattice Noise Types Noise Summation Techniques Reducing artifacts General strategies Antialiasing Snow accumulation and terrain generation Conclusion The Importance of Being Noisy Almost all procedural generation uses some form of noise If image is food, then noise is salt – adds distinct “flavor” Break the monotony of patterns!! Natural scenes and textures Terrain / Clouds / fire / marble / wood / fluids Noise is often used for not-so-obvious textures to vary the resulting image Even for such structured textures as bricks, we often add noise to make the patterns less distinguishable Ех: ToyShop brick walls and cobblestones Why Do We Care About Procedural Generation? Recent and upcoming games display giant, rich, complex worlds Varied art assets (images and geometry) are difficult and time-consuming to generate Procedural generation allows creation of many such assets with subtle tweaks of parameters Memory-limited systems can benefit greatly from procedural texturing Smaller distribution size Lots of variation -
Synthetic Data Generation for Deep Learning Models
32. DfX-Symposium 2021 Synthetic Data Generation for Deep Learning Models Christoph Petroll 1 , 2 , Martin Denk 2 , Jens Holtmannspötter 1 ,2, Kristin Paetzold 3 , Philipp Höfer 2 1 The Bundeswehr Research Institute for Materials, Fuels and Lubricants (WIWeB) 2 Universität der Bundeswehr München (UniBwM) 3 Technische Universität Dresden * Korrespondierender Autor: Christoph Petroll Institutsweg 1 85435 Erding Germany Telephone: 08122/9590 3313 Mail: [email protected] Abstract The design freedom and functional integration of additive manufacturing is increasingly being implemented in existing products. One of the biggest challenges are competing optimization goals and functions. This leads to multidisciplinary optimization problems which needs to be solved in parallel. To solve this problem, the authors require a synthetic data set to train a deep learning metamodel. The research presented shows how to create a data set with the right quality and quantity. It is discussed what are the requirements for solving an MDO problem with a metamodel taking into account functional and production-specific boundary conditions. A data set of generic designs is then generated and validated. The generation of the generic design proposals is accompanied by a specific product development example of a drone combustion engine. Keywords Multidisciplinary Optimization Problem, Synthetic Data, Deep Learning © 2021 die Autoren | DOI: https://doi.org/10.35199/dfx2021.11 1. Introduction and Idea of This Research Due to its great design freedom, additive manufacturing (AM) shows a high potential of functional integration and part consolidation [1]-[3]. For this purpose, functions and optimization goals that are usually fulfilled by individual components must be considered in parallel. -
Receiver Sensitivity and Equivalent Noise Bandwidth Receiver Sensitivity and Equivalent Noise Bandwidth
11/08/2016 Receiver Sensitivity and Equivalent Noise Bandwidth Receiver Sensitivity and Equivalent Noise Bandwidth Parent Category: 2014 HFE By Dennis Layne Introduction Receivers often contain narrow bandpass hardware filters as well as narrow lowpass filters implemented in digital signal processing (DSP). The equivalent noise bandwidth (ENBW) is a way to understand the noise floor that is present in these filters. To predict the sensitivity of a receiver design it is critical to understand noise including ENBW. This paper will cover each of the building block characteristics used to calculate receiver sensitivity and then put them together to make the calculation. Receiver Sensitivity Receiver sensitivity is a measure of the ability of a receiver to demodulate and get information from a weak signal. We quantify sensitivity as the lowest signal power level from which we can get useful information. In an Analog FM system the standard figure of merit for usable information is SINAD, a ratio of demodulated audio signal to noise. In digital systems receive signal quality is measured by calculating the ratio of bits received that are wrong to the total number of bits received. This is called Bit Error Rate (BER). Most Land Mobile radio systems use one of these figures of merit to quantify sensitivity. To measure sensitivity, we apply a desired signal and reduce the signal power until the quality threshold is met. SINAD SINAD is a term used for the Signal to Noise and Distortion ratio and is a type of audio signal to noise ratio. In an analog FM system, demodulated audio signal to noise ratio is an indication of RF signal quality. -
AN10062 Phase Noise Measurement Guide for Oscillators
Phase Noise Measurement Guide for Oscillators Contents 1 Introduction ............................................................................................................................................. 1 2 What is phase noise ................................................................................................................................. 2 3 Methods of phase noise measurement ................................................................................................... 3 4 Connecting the signal to a phase noise analyzer ..................................................................................... 4 4.1 Signal level and thermal noise ......................................................................................................... 4 4.2 Active amplifiers and probes ........................................................................................................... 4 4.3 Oscillator output signal types .......................................................................................................... 5 4.3.1 Single ended LVCMOS ........................................................................................................... 5 4.3.2 Single ended Clipped Sine ..................................................................................................... 5 4.3.3 Differential outputs ............................................................................................................... 6 5 Setting up a phase noise analyzer ........................................................................................................... -
Understanding Noise Figure
Understanding Noise Figure Iulian Rosu, YO3DAC / VA3IUL, http://www.qsl.net/va3iul One of the most frequently discussed forms of noise is known as Thermal Noise. Thermal noise is a random fluctuation in voltage caused by the random motion of charge carriers in any conducting medium at a temperature above absolute zero (K=273 + °Celsius). This cannot exist at absolute zero because charge carriers cannot move at absolute zero. As the name implies, the amount of the thermal noise is to imagine a simple resistor at a temperature above absolute zero. If we use a very sensitive oscilloscope probe across the resistor, we can see a very small AC noise being generated by the resistor. • The RMS voltage is proportional to the temperature of the resistor and how resistive it is. Larger resistances and higher temperatures generate more noise. The formula to find the RMS thermal noise voltage Vn of a resistor in a specified bandwidth is given by Nyquist equation: Vn = 4kTRB where: k = Boltzmann constant (1.38 x 10-23 Joules/Kelvin) T = Temperature in Kelvin (K= 273+°Celsius) (Kelvin is not referred to or typeset as a degree) R = Resistance in Ohms B = Bandwidth in Hz in which the noise is observed (RMS voltage measured across the resistor is also function of the bandwidth in which the measurement is made). As an example, a 100 kΩ resistor in 1MHz bandwidth will add noise to the circuit as follows: -23 3 6 ½ Vn = (4*1.38*10 *300*100*10 *1*10 ) = 40.7 μV RMS • Low impedances are desirable in low noise circuits. -
Noise, Distortion and Mixing Lab
EECS 142 Noise, Distortion and Mixing Lab A. M. Niknejad Berkeley Wireless Research Center University of California, Berkeley 2108 Allston Way, Suite 200 Berkeley, CA 94704-1302 November 25, 2008 1 1 Prelab In this laboratory you will measure and characterize the non-linear and noise properties of your amplifier. If you were not able to get your amplifier to work correctly, a few working amplifiers are available. Even though your amplifier likely incorporates many inductors and capacitors, elements with memory, a simple memoryless power series analysis is still appli- cable if special care is taken in your calculations. In particular, the memoryless portion and filtering effects of the inductors and capacitors can often be separated and analyzed sepa- rately. For instance, if two tones are applied in the band of interest, then the harmonics are heavily attenuated by the LC tuning/matching networks, but the intermodulation products that fall in-band remain unfiltered. Likewise, if your amplifier uses feedback, be sure to calculate the loop gain at the frequency product of interest when analyzing the effect of the feedback on the amplifier performance. 1. Begin by calculating a power series representation for the in-band performance of the amplifier design. Assume that the amplifier is operating in resonance so that many LC elements resonate out and only the resistive parasitic effects remain. 2. From the power series, predict the harmonic powers (2nd, 3rd) and intermodulation powers for a 600 MHz input(s) with -30 dBm input power. If your amplifier center frequency is different, use the actual center frequency for the measurements. -
Digital to Analog, PWM, Stepper Motors
Lecture #19 Digital To Analog, PWM, Stepper Motors 18-348 Embedded System Engineering Philip Koopman Monday, 28-March-2016 Electrical& Computer ENGINEERING © Copyright 2006-2016, Philip Koopman, All Rights Reserved Example System: HVAC Compressor Expansion Valve [http://www.solarpowerwindenergy.org] 2 HVAC Embedded Control Compressors (reciprocating & scroll) • Smart loading and unloading of compressor – Want to minimize motor turn on/turn off cycles – May involve bypassing liquid so compressor keeps running but doesn’t compress • Variable speed for better output temperature control • Diagnostics and prognostics – Prevent equipment damage (e.g., liquid entering compressor, compressor stall) – Predict equipment failures (e.g., low refrigerant, motor bearings wearing out) Expansion Valve • Smart control of amount of refrigerant evaporated – Often a stepper motor • Diagnostics and prognostics – Low refrigerant, icing on cold coils, overheating of hot coils System coordination • Coordinate expansion valve and compressor operation • Coordinate multiple compressors • Next lecture – talk about building-level system level diagnostics & coordination 3 Where Are We Now? Where we’ve been: • Interrupts, concurrency, scheduling, RTOS Where we’re going today: • Analog Output Where we’re going next: • Analog Input •Human I/O • Very gentle introduction to control •… • Test #2 and last project demo 4 Preview Digital To Analog Conversion • Example implementation • Understanding performance • Low pass filters Waveform encoding PWM • Digital way -
Link Budgets 1
Link Budgets 1 Intuitive Guide to Principles of Communications www.complextoreal.com Link Budgets You are planning a vacation. You estimate that you will need $1000 dollars to pay for the hotels, restaurants, food etc.. You start your vacation and watch the money get spent at each stop. When you get home, you pat yourself on the back for a job well done because you still have $50 left in your wallet. We do something similar with communication links, called creating a link budget. The traveler is the signal and instead of dollars it starts out with “power”. It spends its power (or attenuates, in engineering terminology) as it travels, be it wired or wireless. Just as you can use a credit card along the way for extra money infusion, the signal can get extra power infusion along the way from intermediate amplifiers such as microwave repeaters for telephone links or from satellite transponders for satellite links. The designer hopes that the signal will complete its trip with just enough power to be decoded at the receiver with the desired signal quality. In our example, we started our trip with $1000 because we wanted a budget vacation. But what if our goal was a first-class vacation with stays at five-star hotels, best shows and travel by QE2? A $1000 budget would not be enough and possibly we will need instead $5000. The quality of the trip desired determines how much money we need to take along. With signals, the quality is measured by the Bit Error Rate (BER). -
Networking, Noise
Final TAs • Jeff – Ben, Carmen, Audrey • Tyler – Ruiqi – Mason • Ben – Loudon – Jordan, Nick • David – Trent – Vijay Final Design Checks • Optional this week • Required for Final III Playtesting Feedback • Need three people to playtest your game – One will be in class – Two will be out of class (friends, SunLab, etc.) • Should watch your victim volunteer play your game – Don’t comment unless necessary – Take notes – Pay special attention to when the player is lost and when the player is having the most fun Networking STRATEGIES The Illusion • All players are playing in real-time on the same machine • This isn’t possible • We need to emulate this as much as possible The Illusion • What the player should see: – Consistent game state – Responsive controls – Difficult to cheat • Things working against us: – Game state > bandwidth – Variable or high latency – Antagonistic users Send the Entire World! • Players take turns modifying the game world and pass it back and forth • Works alright for turn-based games • …but usually it’s bad – RTS: there are a million units – FPS: there are a million bullets – Fighter: timing is crucial Modeling the World • If we’re sending everything, we’re modeling the world as if everything is equally important Player 1 Player 2 – But it really isn’t! My turn Not my turn Read-only – Composed of entities, only World some of which react to the StateWorld 1 player • We need a better model to solve these problems Client-Server Model • One process is the authoritative server Player 1 (server) Player 2 (client) – Now we -
Test Procedure for Measuring the Noise Figure of Radio Monitoring Receivers
Recommendation ITU-R SM.1838-0 (12/2007) Test procedure for measuring the noise figure of radio monitoring receivers SM Series Spectrum management ii Rec. ITU-R SM.1838-0 Foreword The role of the Radiocommunication Sector is to ensure the rational, equitable, efficient and economical use of the radio-frequency spectrum by all radiocommunication services, including satellite services, and carry out studies without limit of frequency range on the basis of which Recommendations are adopted. The regulatory and policy functions of the Radiocommunication Sector are performed by World and Regional Radiocommunication Conferences and Radiocommunication Assemblies supported by Study Groups. Policy on Intellectual Property Right (IPR) ITU-R policy on IPR is described in the Common Patent Policy for ITU-T/ITU-R/ISO/IEC referenced in Resolution ITU-R 1. Forms to be used for the submission of patent statements and licensing declarations by patent holders are available from http://www.itu.int/ITU-R/go/patents/en where the Guidelines for Implementation of the Common Patent Policy for ITU-T/ITU-R/ISO/IEC and the ITU-R patent information database can also be found. Series of ITU-R Recommendations (Also available online at http://www.itu.int/publ/R-REC/en) Series Title BO Satellite delivery BR Recording for production, archival and play-out; film for television BS Broadcasting service (sound) BT Broadcasting service (television) F Fixed service M Mobile, radiodetermination, amateur and related satellite services P Radiowave propagation RA Radio astronomy RS Remote sensing systems S Fixed-satellite service SA Space applications and meteorology SF Frequency sharing and coordination between fixed-satellite and fixed service systems SM Spectrum management SNG Satellite news gathering TF Time signals and frequency standards emissions V Vocabulary and related subjects Note: This ITU-R Recommendation was approved in English under the procedure detailed in Resolution ITU-R 1.