Wolfgang Koch

Wolfgang Koch
Institute of Electrical and Electronics Engineers | IEEE · SDF

About

636
Publications
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18,342
Citations

Publications

Publications (636)
Article
Random matrices are widely used to estimate the extent of an elliptically contoured object. Usually, it is assumed that the measurements follow a normal distribution, with its standard deviation being proportional to the objects extent. However, the random matrix approach can filter the center of gravity and the covariance matrix of measurements in...
Article
In stochastic estimation problems, we aim to estimate an unknown state of interest given a set of measurements received from noisy sensory devices, such as radar, Light Detection and Ranging (LiDAR), etc. A common model of the measurements random error is white Gaussian noise. This noise model is usually used to derive an estimator of the unknown s...
Article
Full-text available
During Fusion 2019 Conference (https://www.fusion2019.org/program.html), leading experts presented ideas on the historical, contemporary, and future coordination of artificial intelligence/machine learning (AI/ML) with sensor data fusion (SDF). While AI/ML and SDF concepts have had a rich history since the early 1900s—emerging from philosophy and p...
Article
The articles in this special section focus on some recent and ongoing developments of artificial intelligence in the context of data fusion.
Preprint
Full-text available
Grid maps are widely established for the representation of static objects in robotics and automotive applications. Though, incorporating velocity information is still widely examined because of the increased complexity of dynamic grids concerning both velocity measurement models for radar sensors and the representation of velocity in a grid framewo...
Conference Paper
Full-text available
This paper investigates the performance of Kalman filters and batch filters for the orbit determination with the Tracking and Imaging Radar (TIRA) system, developed and operated by Fraunhofer FHR. Dedicated experiments were conducted with the TIRA system in a Beam Park like observation mode. The results were compared with high precision ephemerides...
Conference Paper
The detection and tracking of consumer grade unmanned aerial vehicles is of great interest in recent years due to threats arising from the widespread availability of such devices. Passive radar is considered as a sensor system capable of contributing to this task. %The small radar cross section of such targets, the low transmit power of available...
Conference Paper
This paper presents the Online Adaptive Fuser: OA-Fuser, a novel method for online adaptive estimation of motion and measurement uncertainties for efficient tracking and fusion by applying a system of several estimators for ongoing noise along with the conventional state and state covariance estimation. In our system, process and measurement noises...
Preprint
This paper introduces BAAS, a new Extended Object Tracking (EOT) and fusion-based label annotation framework for radar detections in the context of autonomous driving. Our framework utilizes Bayesian based tracking, smoothing and eventually fusion methods to provide veritable and precise object trajectories along with shape estimation in order to p...
Conference Paper
Full-text available
This paper addresses the problem of multitarget tracking using a network of mobile sensors with unknown positions. In contrast to commonly-used approaches which split the sensor localization and target tracking into two different sub-problems, we propose a holistic approach for joint localiza-tion and tracking. The theory of graphical models is use...
Article
An article in the September 2019 issue of the AES Magazine described the background of the IEEE Historic Milestone to mark the invention and first demonstration of the radar by the German inventor Christian H€ulsmeyer [1]. On 17 May 1904, H€ulsmeyer arranged a demonstration of his invention in K€oln (Cologne), Germany, which was reported in the K€o...
Article
October 2019 will see the inauguration of an IEEE Historic Milestone recognizing the invention and demonstration of a radar by Christian H€ulsmeyer, in Germany in 1904. The IEEE History Committee voted to recommend a milestone proposal that was approved by the IEEE Board of Directors during its June 2019 meeting. The ceremonial inauguration of the...
Article
Extended objects generate a variable number of multiple measurements. In contrast with point targets, extended objects are characterized with their size or volume, and orientation. Multiple object tracking is a notoriously challenging problem due to complexities caused by data association. This paper develops a box particle filter method for multip...
Chapter
Up to the present day, GPS signals are the key component in almost all outdoor navigation tasks of robotic platforms. To obtain the platform pose, comprising the position as well as the orientation, and receive information at a higher frequency, the GPS signals are commonly used in a GPS-corrected inertial navigation system (INS). However, the GPS...
Conference Paper
Full-text available
In this paper, a method for designing optimised search strategies based on principles from quality of service resource management is proposed. Given emitters with approximately known parameters, revisit and dwell times are chosen per frequency band. The goal is to maximise the utility achieved by the emitters' probability of identification under th...
Conference Paper
Full-text available
Bayesian recursive estimation using large volumes of data is a challenging research topic. The problem becomes particularly complex for high dimensional non-linear state spaces. Markov chain Monte Carlo (MCMC) based methods have been successfully used to solve such problems. The main issue when employing MCMC is the evaluation of the likelihood fun...
Conference Paper
This paper presents results of the Canadian-German research project PASSAGES (Protection and Advanced Surveillance System for the Arctic: Green, Efficient, Secure)1 on an advanced surveillance system for safety and security of maritime operations in Arctic areas. The motivation for a surveillance system of the Northwest Passage is the projected gro...
Article
Full-text available
The state estimation plays an important role in analyzing many real world systems. Such systems can be classified into being linear or non-linear, and depending on the statistical properties of the inherent uncertainties as being Gaussian or non-Gaussian. Unlike linear Gaussian systems, a close form estimator does not exist for non-linear/non-Gauss...
Conference Paper
Particle flow filters, also known as Daum-Huang filters (DHF), provide an alternative method for the state estimation of non-linear / non-Gaussian systems, in a Bayesian context. These filters incorporate the measurements in several steps, which is manifested in the form of the gradual update of particles states. Updates are performed by solving an...
Conference Paper
In this paper, we present an innovative calibration procedure to determine the angle misalignments, also known as boresight, between the coordinate systems of an inertial navigation system (INS) and a camera. All currently known approaches integrate positional information from the INS in the optimization process. Thereby, the position errors in the...
Conference Paper
Different signal propagation velocities can be advantageous for passive tracking. For example, electronic and acoustic sensors can be used in conjunction to localize objects emitting electromagnetic waves and sound. In a heterogeneous passive sensor setup involving electromagnetic detection and acoustic bearing sensors, observability is studied, ev...
Conference Paper
In this paper we introduce a new method of deciding, if a trajectory is following a pre-defined path. This is achieved by representing hypotheses as trajectories themselves using Accumulated State Densities. Live tracking data is incorporated into the trajectories via out of sequence processing. Through this, we gain two representations of the sens...
Conference Paper
Full-text available
The optimal non-linear filter estimates can be obtained by solving the Fokker-Planck equation (FPE) for the time propagation, together with the Bayesian measurement inclusion. An issue faced when solving the FPE is the curse of dimen-sionality. Recently, a tensor based approach has been proposed, which is said to be suitable for high dimensional pr...
Conference Paper
Full-text available
This paper considers the problem of trajectory optimization for two platforms which perform bearings only tracking for multiple targets. It is not assumed that the measurements contain identifying features that enable measurements to be associated to targets. Therefore, ghost targets can appear, which strongly affect the resulting error. In compari...
Conference Paper
Heel strikes from walking people generate impulses that propagate as Rayleigh waves that can be measured by seismic sensors. The time of arrival of these waves dependent upon both the location of the sensors and the propagation medium, which is usually not known. Hence, associating measured signals to an individual person is difficult. In this pape...
Conference Paper
Full-text available
The usage of a global positioning system (GPS) corrected inertial navigation system (INS) seems to be advantageous to camera-based pose estimation algorithms for outdoor navigation. The GPS signals lead to a geographical location with an accuracy of a few meters or even up to some centimeters in a setup utilizing correction data. Performing the pos...
Chapter
Ground surveillance comprises track extraction and maintenance of single ground moving vehicles and convoys, as well as low-flying objects such as helicopters or unmanned aerial vehicles (UAVs). By using airborne sensor platforms in stand-off ground surveillance applications, the effect of topographical screening is alleviated, thus extending the s...
Chapter
Target tracking is the estimation of the state of one or multiple, usually moving, objects (targets) based on a time series of measurements. Widely addressed within the Bayesian statistical framework, it requires the modeling of the target state evolution and the measurement process. Information on the constraints posed by the context in which the...
Chapter
The informational basis for making appropriate decisions is provided by situation pictures that electronically represent a dynamically evolving real-world scenario. For the rapidly growing area of civil security applications, exploitation of observational information, sensor data as well as textual reports, critically depends on the availability an...
Article
The discrimination of closely spaced targets is a major challenge in the ground target-tracking domain based on measurements of airborne ground moving target indication radar. Being a standard output of modern radar systems, the measured signal strength of a radar detection can be used to estimate the characteristic mean radar cross section (RCS) o...
Article
The task of tracking targets, that generate more than one measurement per scan appears in several applications such as extended object and group tracking. In this case, the target (or group) extent implies that multiple measurements, drawn according to a spatial probability distribution, are measured per sensor-scan. However, applications exist whe...
Article
Full-text available
Extended objects generate a variable number of multiple measurements. In contrast with point objects, extended targets are characterized with their size or volume. This paper presents a novel Box particle filter approach for extended object tracking in the presence of clutter. The extended object tracking problem is formulated as joint state and pa...
Research
Full-text available
For linear-Gaussian non-deterministic dynamics, that is, systems with non-zero process noise, it is well known that tracklet fusion based on equivalent measurement is optimal only for full communication rate, i.e., if the local posterior probabilities or estimates are communicated and fused after each observation and update time. Despite this const...
Article
In tracking and sensor data fusion applications, the full information on kinematic object properties accumulated over a certain discrete time window up to the present time is contained in the conditional joint probability density function of the kinematic state vectors referring to each time step in this window. This density is conditioned by the t...
Conference Paper
Full-text available
In multiple target tracking target occlusion or shadowing is a common occurrence. A target may be occluded by an existing structure, or in many cases, by another moving target in the environment. In this paper we consider a UWB-based range-only person tracking system. Occlusion regions induced by moving targets in the scenario are defined followed...
Conference Paper
Full-text available
The Ensemble Kalman Filter (EnKF) is a Kalman based particle filter which was introduced to solve large scale data assimilation problems where the state space is of very large dimensionality. It also achieves good results when applied to a target tracking problem, however, due to its Gaussian assumption for the prior density, the performance can be...
Article
Full-text available
The family of pointillist multitarget tracking filters is defined to be the class of filters that is characterized by a joint target-measurement finite point process. The probability generating functional (PGFL) of the joint process is derived directly from the probabilistic structure of the tracking problem. PGFLs exemplify the analytic combinator...
Article
The estimation of the state of a dynamical system from corrupted sensor data is difficult when data association conflicts, possibly unresolved measurements, and a complex system dynamics must be taken into account. With some necessity this problem calls for multiple hypothesis/multiple model estimators. In this context we consider experimental resu...
Article
Before any thoughts of technical realization or scientific reflections on it, all living creatures perform Sensor Data Fusion: They combine sensations from mutually complementary sense organs with their past experiences and the communications they receive from other creatures. By doing so, they generate ???situation pictures??? of their particular...
Article
Full-text available
Detection of cars has a high variety of civil and military applications, e.g., transportation control, traffic monitoring, and surveillance. It forms an important aspect in the deployment of autonomous unmanned aerial systems in rescue or surveillance missions. In this paper, we present a two-stage algorithm for detecting automobiles in aerial digi...
Article
Altered SERT and DAT availabilities during treatment with escitalopram were investigated with [(123)I]2β-carbomethoxy-3β-(4-iodophenyl)tropane (β-CIT) SPECT in a series of patients fulfilling the criteria for unipolar major depressive disorder (MDD). 27 patients (10m, 42±16y) with diagnosis of MDD were recruited for the study. All patients underwen...
Article
In this paper a new interpretation of linear estimation in the context of classical mechanics is presented. In this context, Accumulated State Densities can be interpreted as the Lagrange function of a "least action" principle that provides the expectation vectors for filtering and retrodiction as a solution. The superposition principle, which stat...
Conference Paper
When localizing multiple tag-free targets using ultra-wideband sensors, targets closer to the sensor occlude targets further from the sensor and in turn these targets are not detected. In this paper we first model the occlusion region of each target. Based on this model, targets unresolved in sensor data and occluded by other targets are updated. E...
Article
The task of tracking targets, that generate more than one measurement per scan appears in several applications such as extended object and group tracking. There, the target (or group) extend implies that muliple measurements, drawn according to a spatial probability distribution, are measured per sensor-scan. However, applications exist where targe...
Article
Full-text available
In track fusion, the measurements of individual sensors for each target are processed to generate local state estimates, which are then fused to obtain the global state estimate for the target. When there is no process noise or the fusion rate equals the sensor observation rate, the standard tracklet fusion or equivalent measurement fusion algorith...
Article
The passive non-cooperative localization and tracking of mobile terminals in urban scenarios, called blind mobile localization (BML), is a highly demanding task which occurs for instance in safety, emergency and security applications with non-subscribed phone user locations. Due to the urban environment and physical propagation effects multiple sig...
Article
Living safely and securely is a basic human desire with many facets. Its satisfaction has psychological and societal, but also technical, legal, and economic implications. Moreover, rapid progress in networking sensors producing an ever increasing diversity of information has profoundly transformed the notion of public security. This technological...
Article
Within the general framework of Bayesian reasoning and based on object evolution models and sensor likelihood functions, such as those previously discussed, we proceed along the following lines.
Article
In most cases, not all properties characterizing observed objects in a certain application have the same importance for producing a situation picture or can be inferred by the sensor systems involved. At the very beginning, we have to identify suitable object properties relevant to the underlying requirements, which are called state quantities. In...
Article
Most target tracking algorithms aim at calculating the conditional probability densities p(Xl\Zk) of target states Xl, which describe the available knowledge on the target properties at a certain instant of time tl, given a time series Zk of imperfect sensor data accumulated to time tk.
Article
In several applications, it is necessary to learn more from the sensor data received than the time-varying geolocation of moving objects of interest. Rather, we wish to understand what the objects we observe are, i.e. we aim to learn as much as possible about their attributes in order to be able to classify or even identify them. Many relevant obje...
Article
Advanced signal processing techniques exploit even sophisticated physical phenomena of objects of interest and are fundamental to modern sensor system design.
Article
Modern active phased-array radar [1] is an example of a multifunctional sensor system that requires sophisticated sensor management algorithms for its efficient operation. Such systems call for efficient exploitation of their degrees of freedom, which are variable over a wide range and may be chosen individually for each track. This is especially t...
Article
Complex sensing environments, such as in airborne ground surveillance or reconnaissance in an urban terrain, are increasingly present in modern applications of sensor data fusion. In order to fulfill user requirements even under those challenging conditions, it is not enough to use a broad spectrum of heterogeneous sensor systems and to integrate a...
Conference Paper
Full-text available
For the purpose of tracking maneuverable targets and estimating the maneuver mode, a multiple model filter similar to the interacting multiple model (IMM) filter is used. The dependency of the mode transition probabilities on the state is taken into account. By the use of the information about the mode that is contained in the target state, a faste...
Article
While location-aware services, both in professional and private context, are widely used today, not all the available knowledge is exploited. The predicted path moving objects follow when being guided e.g. by a smartphone, is not used, instead only the current position is taken into account. In this article, we describe how the exploitation of not...
Conference Paper
Full-text available
In this work, we focus on the task of localizing and tracking multiple non-cooperative objects by a passive antenna array and an optical sensor. Both sensor systems are mounted on an unmanned aerial vehicle and collect bearing measurements from objects, whereby the number of the latter is unknown. For localization and tracking, the imprecise but un...
Article
This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able to track multiple targets and estimates the unknown number of targets. Furthermore, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic, and data associatio...
Conference Paper
The distributed Kalman filter requires the measurement covariances of remote radar nodes to be known at all radar nodes. This is not possible for a radar network, as the true measurement covariances depend on the radar-target geometry and the fluctuating signal-to-noise ratio. This paper tackles this problem using the double debiased distributed Ka...
Conference Paper
Full-text available
In this paper, a direct connection between the covariance debiasing methodology for the distributed Kalman (DKF) filter in [1] and the federated Kalman filter is shown. In particular, it can be seen that for a unique choice of the information gain hypothesis of the DKF, the covariance debiasing becomes equivalent to the federated Kalman filter. As...
Article
One of the main challenges in the domain of ground target tracking based on measurements from airborne ground moving target indication (GMTI) radar is the masking of targets due to the Doppler blind zone of the sensor. This blind zone arises from the clutter cancellation by space-time adaptive processing (STAP) to separate moving target returns fro...
Article
This article presents advances in determining the maximum estimation accuracy, as well as estimating the state for a piecewise maneuvering target with unknown maneuver change times, using passively obtained azimuth (bearings only), azimuth rate, and range measurements. We investigate two types of piecewise target motion and calculate the maximum es...