Suboptimal filtering. Part 3 - Limited memory optimal filtering Final report
Linear and nonlinear limited memory optimal filters for computing conditional probability density function
Bailie, A. E.↗
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Program Computes SLM Inputs To Implement Optimal Filters
Minimum Euclidean Distance Optimal Filter (MEDOF) program generates filters for use in optical correlators. Analytically optimizes filters on arbitrary spatial light modulators (SLMs) of such types as coupled, binary, fully complex, and fractional-2pi-phase. Written in C language.
Barton, R. Shane↗
Limited memory optimal filtering.
Limited memory optimal filter theory, output and standard filter divergence due to errors
Jazwinski, A. H.↗
Limited memory optimal filtering.
Limited memory optimal filter theory, output and standard filter divergence due to errors
Jazwinski, A. H.↗
Optimal filtering and filter stability of linear stochastic delay systems
Optimal filtering equations are obtained for very general linear stochastic delay systems. Stability of the optimal filter is studied in the case where there are no delays in the observations. Using the duality between linear filtering and control, asymptotic stability of the optimal filter is proved. Finally, the cascade of the optimal filter and the deterministic optimal quadratic control system is shown to be asymptotically stable as well.
Kwong, R. H.-S.↗
A note on optimal filtering in the presence of unknown biases
This note considers some aspects of the optimal filtering problem for linear processes in the presence of unknown biases in the input and the observations. It is proved via duality that the optimal filtering problem in the presence of an input bias is equivalent to a certain optimal regulator problem incorporating integral feedback. The question of observability of the augmented system used in the state and bias estimation is answered by deriving necessary and sufficient conditions when bias is present (1) in the input, (2) in the observations and (3) both in the input and the observations.
Joshi, S. M.↗
On optimal filtering of GPS dual frequency observations without using orbit information
The concept of optimal filtering of observations collected with a dual frequency GPS P-code receiver is investigated in comparison to an approach for C/A-code units. The filter presented here uses only data gathered between one receiver and one satellite. The estimated state vector consists of a one-way pseudorange, ionospheric influence, and ambiguity biases. Neither orbit information nor station information is required. The independently estimated biases are used to form double differences where, in case of a P-code receiver, the wide lane integer ambiguities are usually recovered successfully except when elevation angles are very small. An elevation dependent uncertainty for pseudorange measurements was discovered for different receiver types. An exponential model for the pseudorange uncertainty was used with success in the filter gain computations.
Eueler, Hans-Juergen↗
Effect of reduced computer precision on a midcourse navigation and guidance system using optimal filtering and linear prediction
Reduced computer precision effect on midcourse navigation and guidance system using optimal filtering and linear prediction
NAVIGATION AND GUIDANCE↗
Nonlinear Motion Cueing Algorithm: Filtering at Pilot Station and Development of the Nonlinear Optimal Filters for Pitch and Roll
Telban and Cardullo have developed and successfully implemented the non-linear optimal motion cueing algorithm at the Visual Motion Simulator (VMS) at the NASA Langley Research Center in 2005. The latest version of the non-linear algorithm performed filtering of motion cues in all degrees-of-freedom except for pitch and roll. This manuscript describes the development and implementation of the non-linear optimal motion cueing algorithm for the pitch and roll degrees of freedom. Presented results indicate improved cues in the specified channels as compared to the original design. To further advance motion cueing in general, this manuscript describes modifications to the existing algorithm, which allow for filtering at the location of the pilot's head as opposed to the centroid of the motion platform. The rational for such modification to the cueing algorithms is that the location of the pilot's vestibular system must be taken into account as opposed to the off-set of the centroid of the cockpit relative to the center of rotation alone. Results provided in this report suggest improved performance of the motion cueing algorithm.
Zaychik, Kirill B.↗
Optimal filtering of overlapped pulses in microcalorimeter data
In this study, we present a general algorithm for processing microcalorimeter data with special applicability to data with high photon count rates. Conventional optimal filtering, which has become ubiquitous in microcalorimeter data processing, suffers from its inability to recover overlapped pulses without sacrificing spectral resolution. The technique presented here was developed to address this particular shortcoming and does so without imposing any assumptions beyond those made by the conventional technique. We demonstrate the performance of the algorithm with a dataset that approximately satisfies these assumptions and which is representative of a wide range of microcalorimeter applications. We also apply the technique to a highly non-linear dataset, examining the impact on performance in the limit that these assumptions break down.
Dallas Wulf↗
Optimal filters - A unified approach for SNR and PCE
A unified approach for a general metric that encompasses both the signal-to-noise ratio (SNR) and the peak-to-correlation (PCE) ratio in optical correlators is described. In this approach, the connection between optimizing SNR and optimizing PCE is achieved by considering a metric in which the central correlation irradiance is divided by the total energy of the correlation plane. The peak-to-total energy (PTE) is shown to be optimized similarly to SNR and PCE. Since PTE is a function of the search values G and beta, the optimal filter is determined with only a two-dimensional search.
Juday, Richard D.↗
Optimal filters for the moving lens effect
We assess the prospects for detecting the moving lens effect using cosmological surveys. The bulk motion of cosmological structure induces a small-scale dipolar temperature anisotropy of the cosmic microwave radiation, centered around halos and oriented along the transverse velocity field. We introduce a set of optimal filters for this signal and forecast that a high significance detection can be made with upcoming experiments. We discuss the prospects for reconstructing the bulk transverse velocity field on large scales using matched filters, finding good agreement with previous work using quadratic estimators.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Optimal filter design subject to output sidelobe constraints
Optimal pulse compression time-invariant filter for signal reception with sidelobe constraints under white noise in radar and communications systems
Athans, M.↗
Application of an optimal filter for inflatable sphere data processing
The improvement in the sphere data processing, concerning the signal to noise ratio, is discussed. Frequency analysis of the radar data is effectuated. It reveals a specific frequency component in the radar angle error, which may originate from the tracking radar mechanism itself. An optimal (Wiener) filter is applied to the radar data in order to suppress the systematic angular error components selectively. Using this technique, a significant improvement in the signal to noise ratio is achieved. The resolution of sphere measurements, previously limited by the length of the polynomial filter in the sphere data processing algorithm, is improved.
Lee, H. S.↗
Desensitized Optimal Filtering and Sensor Fusion Toolkit
Analytical Mechanics Associates, Inc., has developed a software toolkit that filters and processes navigational data from multiple sensor sources. A key component of the toolkit is a trajectory optimization technique that reduces the sensitivity of Kalman filters with respect to model parameter uncertainties. The sensor fusion toolkit also integrates recent advances in adaptive Kalman and sigma-point filters for non-Gaussian problems with error statistics. This Phase II effort provides new filtering and sensor fusion techniques in a convenient package that can be used as a stand-alone application for ground support and/or onboard use. Its modular architecture enables ready integration with existing tools. A suite of sensor models and noise distribution as well as Monte Carlo analysis capability are included to enable statistical performance evaluations.
Karlgaard, Christopher D.↗
Optimal filter design subject to output delobe constraints
The design of filters for detection and estimation in radar and communications systems is considered, with inequality constraints on the maximum output sidelobe levels. A constrained optimization problem in Hilbert space is formulated, incorporating the sidelobe constraints via a partial ordering of continuous functions. Generalized versions (in Hilbert space) of the Kuhn-Tucker and Duality Theorems allow the reduction of this problem to an unconstrained one in the dual space of regular Borel measures. A convergent algorithm is presented for computational solution of the dual problem.
Fortmann, T. E.↗
Optimal filter design subject to output sidelobe constraints - Theoretical considerations
The design of filters for detection and estimation in radar and communications systems is considered, with inequality constraints on the maximum output sidelobe levels. A constrained optimization problem in Hilbert space is formulated, incorporating the sidelobe constraints via a partial ordering of continuous functions. Generalized versions (in Hilbert space) of the Kuhn-Tucker and duality theorems allow the reduction of this problem to an unconstrained one in the dual space of regular Borel measures.
Fortmann, T. E.↗
Optimal filtering and generation of entangled photons for quantum applications in the presence of noise
Filtering is commonly used in quantum optics to reject noise photons, and also to enable interference between independent photons. However, filtering the joint spectrum of photon pairs can reduce the inherent coincidence probability or loss-independent heralding efficiency. Here we investigate filtering for multiphoton applications based on entanglement and interference (e.g., quantum teleportation). We multiplex C-band entangled photons and C-band classical communications into the same long-distance fibers, which enables scalable low-loss quantum networking but requires filtering of spontaneous Raman scattering noise from classical light. Using tunable-bandwidth filters, low-jitter detectors, and polarization filters, we distribute wavelength-degenerate time-bin entangled photons in the C band (1536.5 nm) over 25 km/25 km standard fibers (50 km) each carrying 10 Gbit/s C-band classical data signals. Narrow filtering enables milliwatt-level C-band power, which exceeds the power achieved by comparable studies by roughly an order of magnitude and could feasibly support terabit per second classical rates. We evaluate how performance depends on pump and filter bandwidths, multipair emission, filter shapes, loss, phase matching, and how quantum information is measured. We find a trade-off between reducing noise impact and increasing single-mode purity, and discuss mitigation methods toward optimal multiphoton applications. Importantly, these results apply to noise in free space and in quantum devices (sources, frequency converters, switches, detectors, etc.) and provide insight into filter-induced degradation of single-photon purity and rates even in noise-free environments.
Thomas, Jordan M. [Fermilab; Northwestern U.]↗