Publications
Tagged As
Cluster detection in databases : the adaptive matched filter algorithm and implementation
January 1, 2003
Journal Article
Published in:
Data Mining and Knowledge Discovery, Vol. 7, No. 1, January 2003, pp. 57-79.
Topic:
R&D group:
Summary
Matched filter techniques are a staple of modern signal and image processing. They provide a firm foundation (both theoretical and empirical) for detecting and classifying patterns in statistically described backgrounds. Application of these methods to databases has become increasingly common in certain fields (e.g. astronomy). This paper describes an algorithm (based on statistical signal processing methods), a software architecture (based on a hybrid layered approach) and a parallelization scheme (based on a client/server model) for finding clusters in large astronomical databases. The method has proved successful in identifying clusters in real and simulated data. The implementation is flexible and readily executed in parallel on a network of workstations.
Summary
Matched filter techniques are a staple of modern signal and image processing. They provide a firm foundation (both theoretical and empirical) for detecting and classifying patterns in statistically described backgrounds. Application of these methods to databases has become increasingly common in certain fields (e.g. astronomy). This paper describes an algorithm...
READ MORE
Gust front update algorithm for the Weather Systems Processor (WSP)
July 29, 2002
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-275
Summary
The Gust Front Update Algorithm (GFUP) is part of the gust front product generation chain for the ASR-9 Weather Systems Processor (WSP). GFUP processes gust front detection and position prediction data output by the Machine Intelligent Gust Front Algorithm (MIGFA), and uses an internal timer to schedule generation of updated current and 10- and 20-minute gust front predictions at 1-minute intervals. By substituting appropriate interval gust front forecast data from MIGFA, the locations of gust fronts shown on the user display are updated at a rate that is faster than the radar base data processed by MIGFA. Prior to output, the updated curve position data are smothered by GFUP using a tangent-spline interpolation algorithm. This document provides a general overview and high level description of the GFUP algorithm.
Summary
The Gust Front Update Algorithm (GFUP) is part of the gust front product generation chain for the ASR-9 Weather Systems Processor (WSP). GFUP processes gust front detection and position prediction data output by the Machine Intelligent Gust Front Algorithm (MIGFA), and uses an internal timer to schedule generation of updated...
READ MORE
ASR-9 Weather Systems Processor (WSP) signal processing algorithms
June 25, 2002
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-255
Summary
Thunderstorm activity and associated low-altitude wind shear constitute a significant safety hazard to aviation, particularly during operations near airport terminals where aircraft altitude is low and flight routes are constrained. The Federal Aviation Administration (FAA) has procured several dedicated meteorological sensors (Terminal Doppler Weather Radar (TDWR), Network Expansion Low Level Wind Shear Alert System (LLWAS) at major airports to enhance the safety and efficiency of operations during convective weather. A hardware and software modification to existing Airport Surveillance Radars (ASR-9)-the Weather Systems Processor (WSP)-will provide similar capabilities at much lower cost, thus allowing the FAA to extend its protection envelope to medium density airports and airports where thunderstorm activity is less frequent. Following successful operation demonstrations of a prototype ASR-WSP, the FAA has procured approximately 35 WSP's for nationwide deployment. Lincoln Laboratory was responsible for development of all data processing algorithms, which were provided as Government Furnished Equipment (GFE), to be implemented by the full-scale development (FSD) contractor without modification. This report defines the operations that are used to produce images of atmospheric reflectivity, Doppler velocity and data quality that are used by WSP's meteorological product algorithms to generate automated information on hazardous wind shear and other phenomena. Principle requirements are suppression of interference (e.g. ground clutter, moving points targets, meteorological and ground echoes originating from beyond the radar's unambiguous range), generation of meteorologically relevant images and estimates of data quality. Hereafter, these operations will be referred to as "signal processing" and the resulting images as "base data."
Summary
Thunderstorm activity and associated low-altitude wind shear constitute a significant safety hazard to aviation, particularly during operations near airport terminals where aircraft altitude is low and flight routes are constrained. The Federal Aviation Administration (FAA) has procured several dedicated meteorological sensors (Terminal Doppler Weather Radar (TDWR), Network Expansion Low Level...
READ MORE
PVL: An Object Oriented Software Library for Parallel Signal Processing (Abstract)
January 1, 2002
Conference Paper
Published in:
CLUSTER '01, 2001 IEEE Int. Conf. on Cluster Computing, 8-11 October 2001, p. 74.
Topic:
R&D group:
Summary
Real-time signal processing consumes the majority of the world's computing power Increasingly, programmable parallel microprocessors are used to address a wide variety of signal processing applications (e.g. scientific, video, wireless, medical, communication, encoding, radar, sonar and imaging). In programmable systems the major challenge is no longer hardware but software. Specifically, the key technical hurdle lies in mapping (i.e., placement and routing) of an algorithm onto a parallel computer in a general manner that preserves software portability. We have developed the Parallel Vector Library (PVL) to allow signal processing algorithms to be written using high level Matlab like constructs that are independent of the underlying parallel mapping. Programs written using PVL can be ported to a wide range of parallel computers without sacrificing performance. Furthermore, the mapping concepts in PVL provide the infrastructure for enabling new capabilities such as fault tolerance, dynamic scheduling and self-optimization. This presentation discusses PVL with particular emphasis on quantitative comparisons with standard parallel signal programming practices.
Summary
Real-time signal processing consumes the majority of the world's computing power Increasingly, programmable parallel microprocessors are used to address a wide variety of signal processing applications (e.g. scientific, video, wireless, medical, communication, encoding, radar, sonar and imaging). In programmable systems the major challenge is no longer hardware but software. Specifically...
READ MORE
The radar Correlation and Interpolation (C&I) algorithms deployed in the ASR-9 Processor Augmentation Card (9PAC)
June 29, 2001
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-299
Summary
The Airport Surveillance Radar 9 (ASR-9) is a terminal radar that was deployed by the Federal Aviation Administration (FAA) during the early 1990's at more than 130 of the busiest airports in the United States. The ASR-9 Processor Augmentation Card (9-PAC), developed at MIT Lincoln Laboratory, is a processor board enhancement for the ASR-9 Array Signal Processor (ASP) that provides increases in processing speed, memory size, and programming. The increased capabilities of the 9PAC hardware made it possible for new surveillance algorithms to be developed in software to provide improved primary radar and beacon surveillance performance. The 9PAC project was developed in two phases. Phase I, which addressed the beacon reflection false target problem, was completed, and is currently being deployed nationwide by the FAA on a plug and play basis. Phase II addresses the primary radar surveillance problems, which include automation of the road and ground clutter censoring process, improving the rejection of false targets, and improving the detection and tracking of aircraft targets. The 9PAC also reduces the life-cycle maintenance cost of the ASR-9 in the Phase II configuration, in which a single 9PAC card replaces four ASP cards. This report describes the improvements to the radar Correlation and Interpolation (C&I) process, which is responsible for creating aircraft target reports and filtering out false targets. [Not Complete]
Summary
The Airport Surveillance Radar 9 (ASR-9) is a terminal radar that was deployed by the Federal Aviation Administration (FAA) during the early 1990's at more than 130 of the busiest airports in the United States. The ASR-9 Processor Augmentation Card (9-PAC), developed at MIT Lincoln Laboratory, is a processor board...
READ MORE
The Vector, Signal, and Image Processing Library (VSIPL): an Open Standard for Astronomical Data Processing
December 1, 1999
Abstract
Published in:
Bulletin of the American Astronomical Society, Vol. 31, p.1497
Topic:
R&D area:
R&D group:
Summary
The Vector/Signal/Image Processing Library (VSIPL) is a DARPA initiated effort made up of industry, government and academic representatives who have defined an industry standard API for vector, signal, and image processing primitives for real-time signal processing on high performance systems. VSIPL supports a wide range of data types (int, float, complex, ...) and layouts (vectors, matrices and tensors) and is ideal for astronomical data processing. The VSIPL API is intended to serve as an open, vendor-neutral, industry standard interface. The object-based VSIPL API abstracts the memory architecture of the underlying machine by using the concept of memory blocks and views. Early experiments with VSIPL code conversions have been carried out by the High Performance Computing Program team at the UCSD. Commercially, several major vendors of signal processors are actively developing implementations. VSIPL has also been explicitly required as part of a recent Rome Labs teraflop procurement. This poster presents the VSIPL API, its functionality and the status of various implementations.
Summary
The Vector/Signal/Image Processing Library (VSIPL) is a DARPA initiated effort made up of industry, government and academic representatives who have defined an industry standard API for vector, signal, and image processing primitives for real-time signal processing on high performance systems. VSIPL supports a wide range of data types (int, float...
READ MORE
Estimation of modulation based on FM-to-AM transduction: two-sinusoid case
November 1, 1999
Journal Article
Published in:
IEEE Trans. Signal Process., Vol. 47, No. 11, November 1999, pp. 3084-3097.
Topic:
R&D area:
Summary
A method is described for estimating the amplitude modulation (AM) and the frequency modulation (FM) of the components of a signal that consists of two AM-FM sinusoids. The approach is based on the transduction of FM to AM that occurs whenever a signal of varying frequency passes through a filter with a nonflat frequency response. The objective is to separate the AM and FM of the sinusoids from the amplitude envelopes of the output of two transduction filters, where the AM and FM are nonlinearly combined in the amplitude envelopes. A current scheme is first refined for AM-FM estimation of a single AM-FM sinusoid by iteratively inverting the AM and FM estimates to reduce error introduced in transduction. The transduction filter pair is designed relying on both a time-and frequency-domain characterization of transduction error. The approach is then extended to the case of two AM-FM sinusoids by essentially reducing the problem to two single-component AM-FM estimation problems. By exploiting the beating in the amplitude envelope of each filter output due to the two-sinusoidal input, a closed-form solution is obtained. This solution is also improved upon by iterative refinement. The AM-FM estimation methods are evaluated through an error analysis and are illustrated for a wide range of AM-FM signals.
Summary
A method is described for estimating the amplitude modulation (AM) and the frequency modulation (FM) of the components of a signal that consists of two AM-FM sinusoids. The approach is based on the transduction of FM to AM that occurs whenever a signal of varying frequency passes through a filter...
READ MORE
Shunting networks for multi-band AM-FM decomposition
October 17, 1999
Conference Paper
Published in:
Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 17-20 October 1999.
Topic:
R&D area:
Summary
We describe a transduction-based, neurodynamic approach to estimating the amplitude-modulated (AM) and frequency-modulated (FM) components of a signal. We show that the transduction approach can be realized as a bank of constant-Q bandpass filters followed by envelope detectors and shunting neural networks, and the resulting dynamical system is capable of robust AM-FM estimation. Our model is consistent with recent psychophysical experiments that indicate AM and FM components of acoustic signals may be transformed into a common neural code in the brain stem via FM-to-AM transduction. The shunting network for AM-FM decomposition is followed by a contrast enhancement shunting network that provides a mechanism for robustly selecting auditory filter channels as the FM of an input stimulus sweeps across the multiple filters. The AM-FM output of the shunting networks may provide a robust feature representation and is being considered for applications in signal recognition and multi-component decomposition problems.
Summary
We describe a transduction-based, neurodynamic approach to estimating the amplitude-modulated (AM) and frequency-modulated (FM) components of a signal. We show that the transduction approach can be realized as a bank of constant-Q bandpass filters followed by envelope detectors and shunting neural networks, and the resulting dynamical system is capable of...
READ MORE
A 9PAC system and application programmer's guide
February 16, 1999
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-267
Summary
The ASR-9 Processor Augmentation Card (9PAC) is a custom processing card that provides the ASR-9 system with increased beacon and radar processing performance. This paper describes the system and application software that executes on the prototype board, with an emphasis on the interaction between software modules. The application software on the 9PAC determines the position of radar and beacon target reports, replacing software that previously ran on the ASR-9 Array Signal Processor (ASP). The software is organized as a set of cooperating tasks executing under the control of a real-time operating system, PAC/OS, which provides all the services typical of an embedded kernel such as interrupt handling, pre-emptive multitasking, queues, signals, semaphores, mailboxes, and memory management. The deployment of 9PAC will occur in two phases. The Phase I application replaces only the beacon target detector (BTD) and radar/beacon target merge (MRG) functions of the ASP. The Phase I application consists of two executable programs since Phase I uses only two of the C44 processors on the 9PAC. One program, the housekeeping processor, is responsible for all I/O functions and performs the radar/beacon merge operation. The second progam, the beacon processor, is dedicated to processing the raw beacon replies and generating beacon targets which are then returned to the first processor for the merge operation. The Phase II application consists of three executable programs, one for each of the C44 processors on the 9PAC and performs much of the Phase I functionality and adds primary radar processing. The intent of this paper is to provide the 9PAC software support personnel with sufficient information to implement future enhancements without unintentionally compromising some aspect of the overall system.
Summary
The ASR-9 Processor Augmentation Card (9PAC) is a custom processing card that provides the ASR-9 system with increased beacon and radar processing performance. This paper describes the system and application software that executes on the prototype board, with an emphasis on the interaction between software modules. The application software on...
READ MORE
AM-FM separation using shunting neural networks
October 6, 1998
Conference Paper
Published in:
Proc. of the IEEE-SP Int. Symp. on Time-Frequency and Time-Scale Analysis, 6-9 October 1998, pp. 553-556.
Topic:
R&D area:
Summary
We describe an approach to estimating the amplitude-modulated (AM) and frequency-modulated (FM) components of a signal. Any signal can be written as the product of an AM component and an FM component. There have been several approaches to solving the AM-FM estimation problem described in the literature. Popular methods include the use of time-frequency analysis, the Hilbert transform, and the Teager energy operator. We focus on an approach based on FM-to-AM transduction that is motivated by auditory physiology. We show that the transduction approach can be realized as a bank of bandpass filters followed by envelope detectors and shunting neural networks, and the resulting dynamical system is capable of robust AM-FM estimation in noisy environments and over a broad range of filter bandwidths and locations. Our model is consistent with recent psychophysical experiments that indicate AM and FM components of acoustic signals may be transformed into a common neural code in the brain stem via FM-to-AM transduction. Applications of our model include signal recognition and multi-component decomposition.
Summary
We describe an approach to estimating the amplitude-modulated (AM) and frequency-modulated (FM) components of a signal. Any signal can be written as the product of an AM component and an FM component. There have been several approaches to solving the AM-FM estimation problem described in the literature. Popular methods include...
READ MORE