Adaptive Strategies in Nonlinear Filtering.

Radar systems are used for estimating the position and velocity of aircraft and ships from range and bearing measurements. In this article, we consider two motion models for a civilian aircraft: a constant velocity model and a coordinated turn model. Both kinematics models are written in state-space terms, where the velocity perturbations are modeled by a white noise acceleration model. In order to estimate the aircraft states given noisy measurements obtained from sensor outputs, we follow a Bayesian statistical approach that calculates the estimators of the unknown states. In our simulation, we recreate an air traffic control scenario and implement two nonlinear filtering algorithms in order to perform target tracking of the aircraft. The nonlinear Bayesian-based filters for this target tracking problem are the unscented Kalman filter and the Gauss-Hermite Kalman filter. Finally, the performance of both nonlinear filters is evaluated with a performance metric, root mean squared error, in Monte-Carlo runs.KeywordsTarget trackingUnscented Kalman filterGauss-Hermite Kalman filter

LIDAR (Laser Integrated Radar) is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable. In this paper, the Lainiotis′s multi‐model partitioning methodology and the related approximate but effective nonlinear filtering algorithms are reviewed and applied to LIDAR signal processing. Extensive simulation and performance evaluation of the multi‐model partitioning approach and its application to LIDAR signal processing shows that the nonlinear partitioning methods are very effective and significantly superior to the nonlinear extended Kalman filter (EKF), which has been the standard nonlinear filter in past engineering applications.

Dynamical systems encountered in reality are essentially nonlinear. A number of approaches were propped for nonlinear filter with different accuracy. They are mainly investigated from the Bayesian point of view, and may be classified into three kinds of methods: linearization, statistical approximation and Monte-Carlo simulation (Jazwinski 1970; Tanizaki 1993; Gelb 1994). Very often, linearization of the nonlinear system is done using either a precomputed nominal trajectory or the estimate of the state vector. This second linearization approach is better known as the extended Kalman filter (Jazwinski 1970). Since the solution based on one-step linearization may be poor for a highly nonlinear system, iteration in this case is expected in order to obtain a more accurate estimate. Higher order approaches should probably be taken into account. It should be noted, however, that if the system presents a significant nonlineaaity, even the mean and covariance matrix of the nonlinear filter can be misleading, since the means of the estimated state variables may deviate appreciably from their true parameter values. The basic idea of statistical approximation is to replace a nonlinear function of random variables by a series expansion (Gelb 1994) or to approximate thea posteriori conditional probability density function of the state vector (Sorenson & Stubberud 1968; Kramer & Sorenson 1988). The Monte Carlo simulation technique may be used to determine the mean and covariance matrix of the nonlinear filter (if properly designed), which requires a large sample to obtain statistically meaningful results (see e.g. Brown & Mariano 1989; Carlin et al. 1992; Gelb 1994; Tanizaki 1993)

This paper focuses on the issue of nonlinear data filtering in radar tracking. By through the analysis on nonlinear filters, we find that the accuracy of the extended Kalman filtered (EKF) data image was not ideal for radar tracking data filtering. In our study the unscented Kalman filter (UKF) was introduced to achieve better performance. The evidences show that, while comparing with using EKF, using UKF for radar tracking can get more accurate results because the mean and variance of the nonlinear function can be estimated more accurately with unscented transformation, and the computation complexity is reduced significantly by avoiding to calculate the Jacobian matrix.KeywordsRadar trackingKalman filter (KF)Nonlinear filterUnscented Kalman filter

While agglomerations along the Rhine are confronted with the uncertainties of an increasing flood risk due to climate change, different programs are claiming urban river front sites. Simultaneously, urban development, flood management, as well as navigation and environmental protection are negotiating the border between the river and the urban realm. This produces complex spatial constellations between the river system and the urban realm with a diverse set of interdependencies, where programs have to synergize while adapting to dynamic water levels. Based on an expanding area at risk and the reliance on flood levels to remain within an acceptable spectrum for adaptive measures to be effective, Urban Flood Integration (UFI) involves border negotiations between the river and the urban realm where adaptation and mitigation ideally synergize. Instead of a scientific approach that reduces complexity in order to reach a verifiable question, a post-normal science approach is chosen as an evaluation and working method applied within this research. The working method relies on literature studies, semi-structured interviews and empirical research through repeated site visits. The general heterogeneity of the case studies regarding their planning structure, status and time scales, data availability and the willingness by the agencies involved to provide usable information shapes the formal research structure. Part I serves as a narrative for the case study analysis and for the final conclusions and recommendations in Part II. It is made up of three chapters, where Urban Flood Integration is framed historically, theoretically and strategically within the specific geographic context of the navigable Rhine: Anthropogenic transformations of the Rhine flood plains in the 19th and 20th century have turned formerly wide, often meandering or bifurcating river beds into urbanized embankments along straight, channelled rivers. The perception of the river changed from being dynamic to being controllable. This produced the spatial backdrop for modernist and therefore sectoral developments based on a dialectical relationship between the urban realm and the (river) landscape. Yet, as conversions of former harbours are turning sites outside the flood defence into inner city living quarters, as retention polders are positioned in flood plains with enough damage potential to threaten regional economies, and flood mitigating measures are more viable/effective on site in the middle of the city than in a rural area, site specific negotiations between simultaneous programmatic claims are producing new urban typologies/ecologies that in turn demand and rely on a new methodological approach. Within this research design is considered not only a spatial, but also a strategic tool capable of not only linking different programs, but also different disciplines. Flood Risk Management along the Rhine today combines river expanding measures and adaptive strategies with the existing defensive system to cope with the risk increase as a consequence of previous interventions and developments and fluctuations in water levels due to climate change. Differences in landscapes and urgencies and differences in planning cultures between the Upper and Lower Rhine and the Delta have also led to different strategic approaches. Within this research the innovative capacity of the adaptive and anticipatory water-based approach in the Netherlands provides lessons to be learned specifically regarding spatial quality as a strategic component of water-related projects. In Part II, the investigation of two Dutch and two German urbanized water front developments along different river segments of the Rhine according to their synergetic potential, but also regarding the temporal and spatial interdependencies between the river system as a whole, the regional context as well as the actual water front as the project site, aims to examine the following questions: Between adaptive and mitigative strategies, what is the spectrum of spatial constellations between urban development and flood management within the constraints set by navigation and a (partial) restoration of the dynamic river landscape? How are temporal and spatial interdependencies shaping these projects? Relational diagrams show the reciprocations between urban development and river dynamics of each investigated case study and the respective agencies and processes involved. The case study analysis serves as a basis for recommendations for the architectural and programmatic scope of flood-resilient projects dealing with expansive flood management strategies and respectively a strategic design approach addressing multiple scales and programs. Embedded in an exemplary atlas of the respective typology along the different Rhine segments, the four case studies from south to north are: • Karlsruhe Rappenwört, a steered retention polder along the meandering Upper Rhine • Mainz Zollhafen, a port conversion with flood adaptive housing along the bifurcating Upper Rhine • Nijmegen Lent, a bypass and urban extension based on a dike set back along the Waal • Dordrecht Stadswerven, an urban development outside the dikes in the Delta In summary, differences in landscape, threat and political structures have produced different planning cultures in Germany and the Netherlands in terms of flood management. Both Dutch and German mitigation measures remain path dependent on the defensive system. Yet, whereas the Dutch approach to flood mitigation is holistic in an extended ecological sense and specifically includes spatial quality, in Germany, planning flood-related issues remains part of a sectoral approach where spatial quality is not initially included, bit remains an additional layer towards the end of the project. Confronted with a strong ecological lobby, the focus is to restore the former alluvial forest in niches. Of the six programs defined in the ICPR Atlas, forestry seems the only one capable of taking on river dynamics and transforming accordingly over time. All other programs (settlements, industries, traffic infrastructure, and to some degree agriculture, specifically when ecological flooding is taken into account) remain reliant on defensive measures, and in case of their failure, infrastructural support and adaptation measures. They are, however, not included in a design strategy that explores potentialities. In the light of long-term strategies and programs, the Dutch approach offers a more iterative planning practice that is capable of evolving with the experience gained. Dutch experience and corresponding policy adaptation has further shown that a more permissive planning approach to allow additional programs within Room for the River measures can raise local acceptance and thus reduce negative effects. In Germany, water management agencies avoid projects that could become precedence cases and thus enable repetition. This restrictive approach is a hindrance on the way to larger-scale strategies that rely on pilot projects as testing grounds. The Dutch approach seems to aim for incentives and actually provides them, as the trade-off in the Nijmegen case shows. Moving from a restrictive to a responsive planning approach that includes incentives produces a breeding ground and should always be a central component of any strategy. One of the main findings of this research is, specifically in Germany, the limited availability of information, as well as lacking visualization layers of ongoing programs and projects (which may be an additional indication of the lacking involvement of designers in German spatial flood risk management projects). This research contributes to a broader understanding by providing an atlas of selected flood-adaptation and flood-mitigation typologies along the Rhine between Basel and Rotterdam. Directly adressing the design practice, this research proposes to move from a spatial to a strategic design approach by: -involving architects, landscape architects, urban designers from the initial stage to enable their engagement also in the strategic design of a project; -enabling design to become part of a systemic approach that aims for capacity building and therefore includes ecological, economic and cultural conditions through a transdisciplinary approach; -making the invisible layers visible: Visualize systems/expert information to make them accessible and to enable communication between disciplines; -hosting design competitions in cooperation with local stakeholders bringing people and ideas together to trigger emergence; -applying back-casting strategies to move beyond existing conceptions: design may thus becomes “telescopic” and allow a challenge of existing givens, the visualization of concepts again playing a central role. Two follow-up research projects are proposed: -Development of Design Guidelines for a river segments approach: Evaluation of ongoing or recent mitigation and adaptation projects, but also other river-related developments (e.g. navigation) in an academic research project to define potential emergent capacities between systemic and qualitative elements. In collaboration with the practice, smaller scale pilots as part of existing mitigation programs on a river segment scale could aim to substantiate the findings. -Cost-Benefit-Analysis Spatial Quality: To substantiate the qualitatively developed argument towards Urban Flood Integration (UFI), a cost-benefit analysis of a transdisciplinary layer that is comparable to the measures defined by the Dutch Quality Team for the German Room for the River, which focus today on ecological rejuvenation vs. spatial quality as a secondary aim. The final outcome of the following multiple case-study investigation and the typological atlas provided is seen to be valuable for a number of different organizations, such as governmental and educational institutions dealing with the geospecific context an

Structural testing involves the methodical exercising of a program f according to selected criteria for coverage of the program flowgraph (e.g., branch-coverage or statement-coverage). Conventional strategies rely on the pre-selection of paths sufficient to provide the desired coverage, with input vectors then chosen to execute this collection of paths (Figure 1): While selecting a set P is not difficult, finding X can be most challenging — involving Boolean satisfiability of full path predicates, backward substitution, or symbolic execution of the paths, often composed of numerous decisions and assignments (Prather, 1983). During this process of finding X, however, some of the paths in P may prove to be infeasible (i.e., there are no inputs that will cause traversal of those paths). Then, like it or not, we are forced to return to the development of additional paths for P.With adaptive strategies, on the other hand, we do not require the pre-selection of P; we not only acknowledge the intrinsic interplay between P and X, we exploit it. Adaptive strategies construct P path-by-path using feedback from previous inputs and their paths of execution (Figure 2): X0 = {X0}, Xk = Xk-1∪{xk} P0 = O, Pk = Pk-1∪ {Pk} Here the initial input x0, possibly chosen arbitrarily, will cause the traversal of some path p1. Then at any later stage, G and Pi are compared to find a new input xi to achieve coverage beyond that already attained, leading, of course, to a new path pi+1. Finally, at the conclusion of these iterations, a comparison of G and Pi will indicate that total coverage under the desired criterion has been accomplished.An early adaptive strategy (Kundu, 1979) required a sort of “diagonalization” of all the path predicates available at any stage to find an input x satisfying none of those predicates, thereby assuring a new path generated by f(x). A more recent approach (Prather and Myers, to appear), the path-prefix strategy, makes use of partial paths — “reversible” path prefixes — to find the next input to provide new coverage.That is, in Figure 3 for the case of branch-coverage, if p is a path representative of those already traversed, the reversible prefix q is the part of p to the first decision node that still has an uncovered branch D+. So now an input Xnew is found to traverse q but to deviate from p at D+. At each stage the shortest such prefix among all the paths in Pi is selected for reversal. Of course, additional “collateral” coverage is generally obtained when the resulting full path is traversed.Now, even using conventional means, finding inputs to traverse prefixes is a simpler problem than for traversing entire pre-selected paths. Indeed, work in progress shows that the adaptive approaches in general are less resource-intensive than conventional approaches (Myers, 1986). Moreover, the number of paths finally contained in P is within the theoretical bounds for any path selection procedure available to assure a given type of coverage. The use of a previously traversed prefix and its associated input vector xpray leads to the possibility of employing non-conventional, feedback oriented means to find the input xnew. Having traversed the prefix q, we are “close” to its reversal, allowing for a presumably slight modification of xprev to obtain xnew by such means.But even in the path-prefix strategy, a condition of “relative” infeasibility can occasionally arise. That is, in Figure 3, the branch D+ may be feasible in that some executable path will traverse D+, but not through any of the available prefixes through D. A loosening of the strategy is possible at this point, however, incorporating conventional path/input selection: any partial path traversing D+, and its associated input, will suffice. Working with this partial path to determine xnew will still be easier than with a full pre-selected path.Overcoming any instances of relative infeasibility is one advantage deriving from the interactive nature of adaptive testing. The feedback loop (Figure 2) allows for considerable participation by the user. As another example, the initial input(s) can be chosen to achieve any desired functional (“black box”) testing or to traverse certain paths of particular interest to the user. The resulting coverage is then incorporated in the ensuing iteration of an adaptive strategy.

Data compression is applicable in reducing amount of data to be stored and it can be applied in several data collecting processes, being generated by lossy or lossless compression algorithms. Due to its large amount of data, the use of compression is desirable in ECG signals. In this work, we present the accepted nonlinear iterative partial least squares (NIPALS) method as an option to ECG compression method, as recommended by Nicolosi (1999). In addition, we compare the results based in an adaptive and non-adaptive version of this method, by using the MIT arrhythmia database. As a help to obtain a better comparison, we have developed an abnormality indicator related to possible abnormalities in the waveform and a decision method that helps to choose between adaptive or non-adaptive approach. Results showed that the adaptive approach is better than the non-adaptive approach, for the NIPALS compression algorithm.

The trajectory estimation of a highly maneuvering target is a challenging problem and has practical applications. The interacting multiple model (IMM) filter is a well-established filtering algorithm for the trajectory estimation of maneuvering targets. In this study, we present an overview of IMM filtering algorithms for tracking a highly-maneuverable fighter aircraft using an air moving target indicator (AMTI) radar on another aircraft. This problem is a nonlinear filtering problem due to nonlinearities in the dynamic and measurement models. We first describe single-model nonlinear filtering algorithms: the extended Kalman filter (EKF), unscented Kalman filter (UKF), and cubature Kalman filter (CKF). Then, we summarize the IMM-based EKF (IMM-EKF), IMM-based UKF (IMM-UKF), and IMM-based CKF (CKF). In order to compare the state estimation accuracies of the IMM-based filters, we present a derivation of the posterior Cramér-Rao lower bound (PCRLB). We consider fighter aircraft traveling with accelerations 3g, 4g, 5g, and 6g and present numerical results for state estimation accuracy and computational cost under various operating conditions. Our results show that under normal operating conditions, the three IMM-based filters have nearly the same accuracy. This is due to the accuracy of the measurements of the AMTI radar and the high data rate.

This paper considers the nonlinear system filtering with packet dropouts. We assume that the packet arrived rate is known in advance but the sequence of packet dropouts is unknown. At first, we use the probability-weighted method to achieve a pseudo measurement sequence, and every pseudo measurement is the weighted value of the measurements acquired at the current time step and the prior time step. Some classical nonlinear filtering methods can be used via the pseudo measurement sequence and the dynamic equation of the system, and then the pseudo measurement unscented Kalman filter (PM_UKF) and the pseudo measurement particle filter (PM_PF) are given. This pseudo measurement sequence can be also used in the linear system, and its time complexity is lower than that of Sun's optimal filter at this time. Simulation results show the effectiveness of the proposed algorithms.

Attitude control system plays the important role for to maintain the satellite to desired orientation. To control the satellite it is necessary to do the attitude stabilization. Attitude stabilization achieved by Star sensor, sun sensor, Earth sensors. Attitude control is mainly use for antenna pointing accuracy, camera focus to earth surface and solar panel pointing toward sun. Due to tumbling effects, satellite will rotate all the direction in the space. To maintain the orientation of the satellite it is necessary to design the attitude determination and control. Satellite consider as the rigid body. Inertia matrix describes the rigid body dynamics. The orientation of the satellite determine by Euler angle and Quaternion. The Low earth orbiting satellite will have enormous amount of aerodynamic drag stinking the satellite body and gravitational attraction another problem. Because of that satellite dwell, time is reduced. It means satellite more time spending particular part of the earth. The attitude estimation is measures by the orientation of vectors. Attitude estimation means to find the position and orientation of flying object with respect to the fixed reference of reference. Vector remains considered in the frame of reference to compute for find the orientation of the body of the satellite in the inertial reference system. The Earth is an inertial reference frame, and Satellite is a body frame. Attitude sensor used to measure the satellite orientation in the reference frame. This will help in accurately predicting the orbit deviation and a control system to correct if any by providing the satellite momentum means ‘mass in motion’ changes in a body rapidly in Low earth orbit due to centripetal force acting on a satellite. Attitude control system (ACS) need the numerical simulation to find the required torque demand by the help of difference between reference input (Attitude) signal and feedback signal measure by attitude sensor to trim the control surface maintain the actuator required orientation . The results will consist of two parts the first part consisting of the attitude estimation using Euler angle and Quaternion method, second part consist of estimate the control torque from magnetic torquer and error estimation using non-linear filter (Unscented Kalman Filter) with MATLAB simulation. Â

In this chapter, the adaptation strategy, which is one of the global advertising strategies, is used in the analysis of advertisement. The adaptation approach is based on the fact that nations located in different geographies in the world are structurally and culturally separate from each other, and advertising messages are reshaped according to these differences. The approach aims to cooperate with the country's local agency and adapt the advertisement to the country's cultural characteristics. The study aims to determine how cultural differences are emphasized in global advertising strategies and how these differences are adapted in ads.

Modelling supply chain adaptation for disruptions: An empirically grounded complex adaptive systems approach

Presents the results obtained in our research about application of modern nonlinear filtering techniques to GPS based position estimation. The stand-alone GPS based position estimation problem using GPS pseudo-range and Doppler shifts measurements are described. A model for position and velocity estimation are developed. The model is nonlinear and has variable measurement number for coping with an arbitrary number of satellites. Over the last 20-30 years, the extended Kalman filter (EKF) has become the algorithm of choice in numerous nonlinear estimation and machine learning applications. In this work the use of an alternative filter: the unscented Kalman filter (UKF) is proposed. The first experimental results that comprise the comparison of estimation results obtained with a simple model using different filters are then presented. Future research directions are also discussed.

The adaptive routing approach has been expected as a promising way to improve network performance by utilizing available network bandwidth. Previous adaptive routing strategies in wormhole-routed multicomputer networks restrict the routing of messages by the routing algorithm to prevent deadlock. This results in low degree of adaptivity and low utilization of physical or virtual channels. In this paper, we examine the possibility of performing restriction-free adaptive routing in wormhole-routed networks as an approach to further improving the performance of these networks. A new flow control policy, called message cutting-in, is proposed, and two adaptive routing strategies are presented. Freedom of communication deadlock is achieved by the proposed flow control policy. The proposed adaptive routing strategies do not restrict routing and maximally utilize the physical and virtual channels. Simulation results show that the restriction-free adaptive routing approach is promising from the fact that it has the lowest latency and highest throughput depending on the number of virtual channels per physical channel and patterns of message traffic.

Traditional village roles and gender shape Samoan perceptions of climate change