Inertial sensing based on cold atom technologies has been proposed as a possible answer to the limited accuracy of current inertial navigation systems. Cold atom technologies offer measurements of inertial quantities that have unprecedented precision and accuracy. However, sensor accuracy is only one of the factors that limit the performance of purely inertial navigation systems. This paper reviews the possible benefits that cold atom quantum sensing may offer in navigation, and discusses a specific example where cold atom gravity gradiometers can be used to augment a standard inertial navigation system through gravitational map-matching.
We describe how the use of multiple-camera imaging systems provides an interesting alternative imaging modality to conventional single-aperture imaging, but with a different challenge: to computationally integrate diverse images while demonstrating an overall system benefit. We report the use of super-resolution with arrays of nominally identical longwave infrared cameras to yield high-resolution imaging with reduced track length, while various architectures enable foveal imaging, 4π and 3D imaging through the exploitation of integral imaging techniques. Strikingly, multi-camera spectral imaging using a camera array can uniquely demonstrate video-rate imaging, high performance and low cost.
Tracking a large number of small targets is a challenging task. This work considers tracking approximately 3000
micron-sized particles in a complex plasma. Inter-particle screened-Coulomb interactions increase the complexity
of the tracking problem, which is further complicated by highly nonlinear dynamics - a shock wave. Subsets
of the particles are tracked concurrently by Interacting Multiple Model estimators, with the results combined
off-line. State estimation is performed by an extended Kalman filter. Estimator performance is quantified on
synthetic data, with discussion focussing on aspects of the Interacting Multiple Model.
This paper presents the results of an integrated target tracking, pursuit and intercept strategy. It is designed to maximize
the overlap between the engagement envelope of a data linked weapon and the possible predicted locations of an agile
target. Once the target track has been initialized, a Markov Model calculates all possible locations of the target up to the
time of intercept, approximately 30 seconds from launch. These locations and associated probabilities are updated during
the tracking process. This includes target maneuvers, which are detected using an IMM estimator. The engagement
envelope is maximized at fixed points in time. In doing so the intercept decision is delayed until, there is a high
probability of a successful interception.
When tracking a target particle that is interacting with nearest neighbors in a known way, positional data of the
neighbors can be used to improve the state estimate. Effects of the accuracy of such positional data on the target
track accuracy are investigated in this paper, in the context of dusty plasmas. In kinematic simulations, notable
improvement in the target track accuracy was found when including all nearest neighbors in the state estimation
filter and tracking algorithm, whereas the track accuracy was not significantly improved by higher-accuracy
measurement techniques. The state estimation algorithm, involving an extended Kalman filter, was shown to
either remove or significantly reduce errors due to "pixel-locking". For the purposes of determining the precise
particle locations, it is concluded that the simplified state estimation algorithm can be a viable alternative to
using more computationally-intensive measurement techniques.
FLIR images are essential for the detection and recognition of ground targets. Small targets can be enhanced using super-resolution
techniques to improve the effective resolution of the target area using a sequence of low-resolution images.
However, when there is significant cloud cover, several problems can arise: clouds can obscure a target (partially or
fully), they can affect the accuracy of image registration algorithms, and they can reduce the contrast of the object
against the background. To reconstruct an image in the presence of cloud cover, image correlation metrics from optical
flow and a robust super-resolution algorithm have been used to compile a 'best' frame.
Complex (dusty) plasmas - consisting of micron-sized grains within an ion-electron plasma - are a unique vehicle for
studying the kinematics of microscopic systems. Although they are mesoscopic, they embody many of the major
structural properties of conventional condensed matter systems (fluid-like and crystal-like states) and they can be used
to probe the structural dynamics of such complex systems. Modern state estimation and tracking techniques allow
complex systems to be monitored automatically and provide mechanisms for deriving mathematical models for the
underlying dynamics - identifying where known models are deficient and suggesting new dynamical models that better
match the experimental data. This paper discusses how modern tracking and state estimation techniques can be used to
explore and control important physical processes in complex plasmas: such as phase transitions, wave propagation and
This paper discusses the problem of assigning tasks to a variety of differently-configured aircraft - aircraft of different
types and carrying very different weapon loads. A multi-objective optimization algorithm is proposed which takes into
account all of the relevant properties of the aircraft and the available weapons. Specifically, it includes limitations due to
the aircraft's speed, time on station and the number of weapons available. The algorithm also allows for the need to
define different priorities for different targets and requirements for co-operative laser designation for certain targets. The
paper also discusses the need for supplementary algorithms to validate the optimal solution proposed by the assignment
This paper uses super-resolution methods to detect small objects in infrared image sequences from a simulated airborne
platform, using image registration techniques for automatic sightline stabilisation. The scene consists of multiple layers,
corresponding to a static background scene and layers of cloud cover at varying heights. The motivation is to evaluate
the performance of super-resolution methods in the presence of three-dimensional structured infrared clutter.
This paper describes a novel set of algorithms that allows indoor activity to be monitored using data from very low
resolution imagers and other non-intrusive sensors. The objects are not resolved but activity may still be determined.
This allows the use of such technology in sensitive environments where privacy must be maintained. Spectral un-mixing
algorithms from remote sensing were adapted for this environment. These algorithms allow the fractional contributions
from different colours within each pixel to be estimated and this is used to assist in the detection and monitoring of small
objects or sub-pixel motion.
In this paper, we consider the control of two qubit systems in the presence of a weak measurement. In particular
we consider how Hamiltonian feedback can be applied to two qubit systems, both in the case where only one
qubit is measured, and in the case where a joint measurement is made of both qubits. We consider how the rate
of entanglement can be increased by using a joint measurement and feedback, and also how information can be
gathered about one qubit by measuring the other.
In this paper we consider feedback control algorithms for the deterministic purification of a bipartite state
consisting of two qubits, when the observer has access to only one of the qubits. We show that Hamiltonian
feedback control can be used to produce deterministic evolution of the purity of either qubit individually, or both
In recent years, closed circuit cameras have become a common feature of urban life. There are environments however
where the movement of people needs to be monitored but high resolution imaging is not necessarily desirable: rooms
where privacy is required and the occupants are not comfortable with the perceived intrusion. Examples might include
domiciliary care environments, prisons and other secure facilities, and even large open plan offices. This paper
discusses algorithms that allow activity within this type of sensitive environment to be monitored using data from low
resolution cameras (ones where all objects of interest are sub-pixel and cannot be resolved) and other non-intrusive
sensors. The algorithms are based on techniques originally developed for wide area reconnaissance and surveillance
applications. Of particular importance is determining the minimum spatial resolution that is required to provide a
specific level of coverage and reliability.
The reliable detection and tracking of missile plumes in sequences of infrared images is a crucial factor in developing
infrared missile warning systems for use in military and civil aircraft. This paper discusses the development of a set of
algorithms that allow missile plumes to be detected, tracked and classified according to their perceived motion in the
image plane. The aim is to classify the missile motion so as to provide an indication of the guidance law which is being
used and, hence, to determine the type of missile that may be present and allow the appropriate countermeasures to be
deployed. The algorithms allow for the motion of the host platform and they determine the missile motion relative to the
fixed background provided by the scene. The tracks produced contain sufficient information to allow good
discrimination between several standard missile types.
This paper discusses the use of continuous weak measurement and quantum feedback for the rapid purification
of the quantum state of a model solid state qubit: a superconducting Cooper pair box. The feedback algorithm
uses Jacobs' rapid purification protocol, which starts with a completely mixed state and applies controls to rotate
the qubit Bloch vector onto the plane orthogonal to the measurement axis. This rotation maximises the rate
of increase of the average purity of the state but can require large changes in the control fields to produce the
required rotation. Since solid state qubits have finite controls and feedback channels have limited bandwidth,
such rotations may not be practical. This paper applies Jacobs' protocol to the Cooper pair box with realistic
Optical flow fields can be used to recover some components of the camera ego-motion such as velocity and angular velocity. In this paper, we discuss the use of optical flow fields to estimate the relative orientation of two imagers with non-overlapping fields of view. The algorithms proposed are based on a spherical alignment technique which is closely related to rapid transfer alignment methods used to align aircraft inertial navigation systems. Of particular importance is the relationship between the accuracy of the optical flow field (which is dependent upon the complexity of the scene and the resolution of the cameras) and the accuracy of the resultant alignment process.
Infrared cameras can detect the heat signatures of missile plumes in the mid-wave infrared waveband (3-5 microns) and are being developed for use, in conjunction with advanced tracking algorithms, in Missile Warning Systems (MWS). However, infrared imagery is also liable to contain appreciable levels of noise and significant levels of thermal clutter, which can make missile detection and tracking very difficult. This paper discusses the use of motion-based methods for the detection, identification and tracking of missiles: utilising the apparent motion of a missile plume against background clutter. Using a toolbox designed for the evaluation of missile warning algorithms, algorithms have been developed, tested and evaluated using a mixture of real, synthetic and composite infrared imagery
This paper examines the benefits of using reconnaissance and targeting imagery in the delivery of air-to-ground guided munitions. In particular, the paper considers the use of third-party imagery to improve the accuracy of scene-matching object localisation algorithms and to improve the delivery accuracy of air-launched seeker-guided weapons. The analysis focuses on a simulated engagement, consisting of an infrared imager placed on an airborne reconnaissance platform, a fast-jet delivery aircraft equipped with a modern electro-optical targeting pod, a seeker-guided weapon model, and a ground target moving in a highly cluttered environment. The paper assesses different strategies for utilizing the target position data from the three imaging systems (reconnaissance, targeting pod and weapon seeker).
In this paper, we consider a natural generalisation of classical proportional navigation guidance for quantum information processing devices. We demonstrate how standard guidance laws can be modified to allow the efficient control of the quantum state of an example qubit. We consider an example experimental system: a Josephson charge qubit (Cooper pair box). The quantum guidance algorithm is assessed in an open-loop control system based on the standard bias fields present in the device, without the need for any additional external fields (such as microwave 'pump' fields, which are often used to drive these charge devices into excited states).
Multiple camera systems have been considered for a number of applications, including infrared (IR) missile detection in modern fast jet aircraft, and soldier-aiding data fusion systems. This paper details experimental work undertaken to test image-processing and harmonisation techniques that were developed to align multiple camera systems. This paper considers systems where the camera properties are significantly different and the camera fields of view do not necessarily overlap. This is in contrast to stereo calibration alignment techniques that rely on similar resolution, fields of view and overlapping imagery. Testing has involved the use of two visible-band cameras and attempts to harmonise a narrow field of view camera with a wide field of view camera. In this paper, consideration has also been given to the applicability of the algorithms to both visual-band and IR based camera systems, the use of supplementary motion information from inertial measurement systems and consequent system limitations.
Traditional missile warning systems (MWSs) have tended to use the ultra-violet waveband, where the ambient intensity levels tend to be low and the resultant false alarm rate is comparatively small. The development of modern infrared imagers has generated interest in the use of infrared imagers in MWSs. Infrared cameras can detect the heat signatures of missile plumes, which peak in the mid-wave (3-5 micron) infrared band, but they can also contain appreciable levels of noise: including intermittent defects that are of the same size as the potential targets. Typically, both missiles and defects will only occupy a few pixels in each image. This paper reviews a project concerned with developing an MWS algorithm toolbox for use in evaluating infrared MWSs. In particular, the paper discusses some of the main problems associated with detecting and tracking missiles in infrared imagery from a moving platform in the presence of localised image noise.
In this paper, we propose a technique to characterise the energy level structure of a superconducting charge qubit. The technique relies on the backreaction of a solid-state qubit on its environment and the incoherent transfer of energy from a high frequency mode to a low frequency mode due to the stochastic transitions of the qubit between energy eigenstates. We consider a coupled system consisting of a model charge qubit and several classical degrees of freedom. The qubit is coupled to three electromagnetic modes: a low frequency bias field, a higher frequency mode (which is used to pump the qubit from the ground state to an excited state), and a lossy reservoir (which represents the cavity that contains the qubit and control fields). The reservoir provides a mechanism to allow the qubit to dissipate energy and to induce spontaneous decays from an excited state into the ground state. We show that these spontaneous decays can have a significant effect on the noise in the classical bias field, and that this noise can be used to characterise the energy level structure of the qubit.
This paper reviews a research program aimed at extracting and utilizing object localization information from sequences of visible band and infrared imagery. The techniques are entirely passive and are based on the relative positions of objects and features taken from a pre-prepared scene database. The techniques used in this project are based on existing techniques for navigation by Scene Matching and Area Correlation (SMAC) and have been adapted for the object localisation task. The paper also considers the use of a Multiple Hypothesis Tracking (MHT) system for the automatic tracking of the known ground features.
Most modern fast jet aircraft have at least one infrared camera, a Forward Looking Infra Red (FLIR) imager. Future aircraft are likely to have several infrared cameras, and systems are already being considered that use multiple imagers in a distributed architecture. Such systems could provide the functionality of several existing systems: a pilot flying aid, a modern laser designator/targeting system and a missile approach warning system. This paper considers image-processing techniques that could be used in a distributed aperture vision system, concentrating on the harmonisation of high resolution, narrow field of view cameras with low-resolution cameras with wide fields of view. In this paper, consideration is given to the accuracy of the registration and harmonisation processes in situations where the complexity of the scene varies over different terrain types, and possible use of supplementary motion information from inertial measurement systems.
The Kalman filter, which is optimal with respect to Gaussian distributed noisy measurements, is commonly used in the Multiple Hypothesis Tracker (MHT) for state update and prediction. It has been shown that when filtering noisy measurements distributed with asymptotic power law tails the Kalman filter underestimates the state error when the tail exponent is less than two and overestimates it when the tail exponent is greater that two. This has severe implications for tracking with the MHT which uses the estimated state error for both gating and probability calculations. This paper investigates the effects of different tail exponent values on the processes of track deletion and creation in the MHT.
There are a number of systems that are currently being considered as candidates for the construction of qubits, quantum logic gates and quantum computers. Some of the systems, notably atoms in magnetic traps and nuclear magnetic resonance (NMR) systems, have had some success in performing the elementary operations that would be required in large-scale quantum computer. However, these systems are not necessarily seen as viable technologies for quantum computing in the longer term. The recent demonstration of macroscopic coherence in a superconducting ring (consisting of a thick superconducting ring containing one or more Josephson weak link devices) has added significant weight to the idea of using superconducting persistent current devices (SQUIDs) in quantum logic systems. In this paper, we consider one aspect of the quantum mechanical SQUID, the nonlinear effect of SQUID on the classical control parameters, and we discuss how it may influence the construction and design of quantum logic gates based on SQUID devices. In particular, we look at problems associated with fixing the classical magnetic flux bias for a quantum mechanical SQUID at, or near, a quantum mechanical transition or resonance.
Proc. SPIE. 4714, Acquisition, Tracking, and Pointing XVI
KEYWORDS: Weapons, Detection and tracking algorithms, Control systems, Computer simulations, Monte Carlo methods, Navigation systems, Target recognition, Imaging infrared seeker, Thermal modeling, Systems modeling
This paper considers the effect of two operational constraints on the size of the release envelope for an air- launched seeker-guided weapon: a requirement for a specified terminal accuracy (as determined by the Circular Error Probable (CEP)) and the requirement for carefree handling (i.e., an insensitivity to release conditions within a specified range of delivery parameters). The system considered in the paper is an air-launched, unpowered weapon with an autonomous guidance capability, provided by an infrared seeker and an inertial navigation system. The weapon is modeled using a six degree-of-freedom ballistic simulation with a simulated infrared seeker and a set of simple target detection algorithms. The paper compares the effect of carefree handling requirements on the size of the weapon's release envelope for two standard delivery profiles (low-level toss delivery and medium-level delivery) and for different requirements on the terminal accuracy.
Proc. SPIE. 4731, Sensor Fusion: Architectures, Algorithms, and Applications VI
KEYWORDS: Target detection, Detection and tracking algorithms, Sensors, Matrices, Error analysis, Monte Carlo methods, Target recognition, Filtering (signal processing), Global Positioning System, Data fusion
This paper examines the requirement for accurate estimates of the statistical correlations between measurements in a distributed air-to-ground targeting system. The study uses results from a distributed multi-platform targeting simulation based on a level-1 data fusion system to assess the extent to which correlated measurements can degrade system performance, and the degree to which these effects need to be included to obtain a required level of accuracy. The data fusion environment described in the paper incorporates a range of target tracking and data association algorithms, including several variants of the standard Kalman filter, probabilistic association techniques and Reid's multiple hypothesis tracker. A variety of decentralized architectures are supported, allowing comparison with the performance of equivalent centralized systems. In the analysis, consideration is given to constraints on the computational complexities of the fusion system, and the availability of estimates of the measurement correlations and platform-dependent biases. Particular emphasis is placed on the localisation accuracy achieved by different algorithmic approaches and the robustness of the system to errors in the estimated covariance matrices.
The accuracy with which an object can be localized is key to the success of a targeting system. Localization is generally achieved by a single sensor, most notably Synthetic Aperture Radar (SAR) or an Infra-Red (IR) device, supported by an Inertial Navigation System (INS) and/or a Global Positioning System (GPS). Future targeting systems are expected to contain (or to have access to data from) multiple sensors, thus enabling data fusion to be conducted and an improved estimate of target location to be deduced. This paper presents a sensor fusion testbed for fusing data from multiple sensors. Initially, a simple, optimal static fusion scheme is illustrated, then focusing on air-to-ground targeting applications example results are given for single and multiple platform sorties involving a variety of sensor combinations. Consideration is given to the most appropriate sensor mix across single and multiple aircraft, as well as architectural implementation issues and effects. The sensitivity of the fusion method to key parameters is then discussed before some conclusions are drawn about the behavior, implications and benefit of this approach to improving targeting.
This paper considers the behavior of a model persistent current qubit in the presence of a time-dependent electromagnetic field. A semi-classical approximation for the electromagnetic field is used to solve the time- dependent Schrodinger equation (TDSE) for the qubit, which is treated as a macroscopic quantum object. The qubit is describe3d by a Hamiltonian involving the enclosed magnetic flux (Phi) and the electric displacement flux Q, which obey the quantum mechanical commutation relation. The paper includes a brief summary of recent work on quantum mechanical coherence in persistent current circuits, and the solution of the TDSE in superconducting rings. Of particular interest is the emergence of strongly non-perturbative behavior that corresponds to transitions between the energy levels of the qubit. These transitions are due to the strong coupling between the electromagnetic fields and the superconducting condensate and can appear at frequencies predicted by conventional methods based on perturbations around the energy eigenstate of the time-independent system. The relevance of these non-perturbative processes to the operation of quantum logic gates based on superconducting circuits and the effect of the resultant non linearities on the environmental degrees of freedom coupled to the qubit are considered.
The accuracy of aircraft/weapon navigation systems has improved dramatically since the introduction of global positioning systems and terrain-referenced navigation systems into integrated navigation suites. Future improvements, in terms of reliability and accuracy, could arise from the inclusion of navigation systems based on the correlation of known ground features with imagery from a visual band or infrared sensor, often called scene matching and area correlation or scene-referenced navigation. This paper considers the use of multi-platform fusion techniques to improve on the performance of individual scene-referenced navigation systems. Consideration is also given to the potential benefits of multi-platform fusion for scene-referenced object localization algorithms that could be used in association with infrared targeting aids.