Distributed Radar-aided Vehicle-to-Vehicle Communication

Establishing high-rate vehicle-to-vehicle (V2V) linkswith narrow beamwidth is challenging due to the varying networktopology. A too narrow beam may miss the intended receiver,while a too broad beam leads to SNR loss. We propose toharness the high accuracy of radar detections to establish V2V links. In particular, we develop a distributed method where eachvehicle associates local radar detections with GPS informationcommunicated by nearby vehicles. The method relies on thetransformation of relative to global coordinates, the definition ofa suitable metric, and solving an optimal assignment problem. Wedemonstrate that the proposed approach avoids time-consumingchannel estimation and provides high SNR, under the conditionthat reliable relative and absolute location information is present

Synchronization-free radchat for automotive radar interference mitigation

Automotive radar interference mitigation is expected to be inherent in all future ADAS and AD vehicles. Joint radar communications is a candidate technology for removing this interference by coordinating radar sensing through communication. Coordination of radars requires strict time synchronization among vehicles, and our formerly proposed protocol (RadChat) achieves this by a precise absolute time, provided by GPS clocks of vehicles. However, interference might appear if synchronization among vehicles is lost in case GPS is spoofed, satellites are blocked over short intervals, or GPS is restarted/updated. Here we present a synchronization-free version of RadChat (Sync-free RadChat), which relies on using the relative time for radar coordination, eliminating the dependency on the absolute time provided by GPS. Simulation results obtained for various use cases show that Sync-free RadChat is able to mitigate interference without degrading the radar performance

Comparison of Automotive FMCW and OFDM Radar Under Interference

Automotive radars are subject to interference in spectrally congested environments. To mitigate this interference, various waveforms have been proposed. We compare two waveforms (FMCW and OFDM) in terms of their radar performance and robustness to interference, under similar parameter settings. Our results indicate that under proper windowing both waveforms can achieve similar performance, but OFDM is more sensitive to interference

Radar Interference Mitigation for Automated Driving: Exploring Proactive Strategies

Autonomous driving relies on a variety of sensors, especially on radars, which have unique robustness under heavy rain/fog/snow and poor light conditions. With the rapid increase of the amount of radars used on modern vehicles, where most radars operate in the same frequency band, the risk of radar interference becomes a compelling issue. This article analyses automotive radar interference and proposes several new approaches, which combine industrial and academic expertise, toward the path of interference-free autonomous driving

Practical Automotive Applications of Cramer-Rao Bound Analysis

The Cram\ue9r-Rao lower bound places a bound, in a mean squared sense, on the performance of all unbiased estimators. In this paper, as a base for discussion, we provide a straight forward derivation of such bounds for estimators of mobile node positions, operating on observations of distances between entities in an asynchronous network. While Cram\ue9r-Rao bound analysis is very common in the positioning community, it is mostly used for analytical evaluation of various estimators, for comparison purposes and for sensor information fusion. In this work, we present some more commercial and practical applications of these tools for performance evaluation. We first discuss the deployment of beacons throughout a transportation infrastructure as a first step towards providing global automotive, possibly GPS augmented, positioning services with applications such as collision warning and collision avoidance. We then move on to describe how the cost associated with the deployment of such beacons can be drastically reduced through relying on inter-node range measurements and a dynamic beaconing scheme we call the lighthouse scheme. We also present a method for complexity reduction in the estimation of relative node coordinates and evaluation of Cram\ue9r-Rao performance measures. \ua92005 IEEE

Positioning and Tracking in Asynchronous Wireless Sensor Networks

This thesis deals with the problem of locating mobile nodes in anasynchronous wireless communication network, i.e., a wireless network of mobileterminals where some or all nodes do not have access to a global time reference.A strong focus lies on reducing the complexity associated with straight forwardclassical algorithms of node coordinate estimation. The thesis is based on anumber of previously published papers, listed in the introductory chapter.Two complexity reducing data preprocessing methods are presented. Bothpreprocessors achieve a complexity reduction through a cancellation of unknownclock-offsets from the estimation problem. Based on a concept of invariantpreprocessors, we show how the individual unknown clock-offsets at some or allnodes in the network may be discarded from the estimation problem, without anydegradation of the asymptotic performance bounds of the positioning problem.We further present two, fully distributed, sub-optimal positioning algorithmsthat operate on a set of asynchronous delay measurements. The first, called thekernel algorithm, reduces complexity by a divide and conquer approach. Thesecond algorithm is based on a mechanical analogy of the positioning problem. Weevaluate the performance of both algorithms, in terms of the mean-squaredpositioning error, by computer simulation. The performance of the kernelalgorithm is found to lie on the order of the delay measurement accuracy, whilethe second algorithm is shown to attain the Cram\ue9r-Rao lower bound under a setof reasonable assumptions.In the last part of the thesis, a novel tracking filter is proposed to reducethe complexity associated with tracking maneuvering objects in a wirelessnetwork. The tracking filter is based on a classical Kalman filter, but usesadditional information, supplied by the tracked node, to aid in the trackingprocess. One drawback associated with this type of approach to tracking is thepossibility of an unstable filter. We argue that the implementation can be maderobust using very simple alterations. Further, we argue that the classicalmean-squared-error performance measure is not fully appropriate for delaysensitive applications, and introduce a novel performance measure called thetime margin measure, suitable for evaluation of tracking algorithms that operateunder latency constraints. We discuss the merits of our proposed trackingfilter, with respect to this new performance measure, as compared to a classicalKalman implementation

Algorithms and Models for Positioning and Scheduling in Wireless Sensor Networks

This thesis considers two problems related to wirelesssensor networks.The first (and main) considered problem is the inference of sensornode positions based on transmissions of RF signals between sensornodes and/or between sensor nodes and fixed reference nodes. Westudy the Cram\ue9r-Rao lower bound on positioning errors inasynchronous wireless sensor networks, and propose positioningalgorithms tailored for implementation in these types of networks.In addition to positioning algorithms, we also study algorithmsfor the estimation of distance between network transceivers basedon transmitted wide-band RF signals, and consider the interactionbetween the ranging and the positioning algorithm. In thealgorithm design, we aim for low complexity and robustness againstthe most common types of error sources, including errors caused byblocked (non-line-of-sight) RF channels, and/or multipathpropagation. On a side-track, we study the feasibility ofcharacterizing the surrounding environment in which a wide-bandwireless sensor network is deployed. This characterization is donein terms of the approximate location of reflective objects thatgenerate significant multi-path components and/oramplify-and-forward relays.The second problem we consider is a scheduling problem thatappears not only in wireless sensor networks, but also in otherwireless networks. We propose a relatively simple model forpacket-loss in a Rayleigh fading environment, and use this modelin an attempt to schedule transmissions in the network so as tominimize the average probability of packet-loss. Since wirelesssensor nodes often only have a limited energy source, and packetretransmissions consume energy, this problem is especiallyimportant in the context of wireless sensor networks

Algorithms and Models for Positioning and Scheduling in Wireless Sensor Networks

This thesis considers two problems related to wirelesssensor networks.The first (and main) considered problem is the inference of sensornode positions based on transmissions of RF signals between sensornodes and/or between sensor nodes and fixed reference nodes. Westudy the Cram\ue9r-Rao lower bound on positioning errors inasynchronous wireless sensor networks, and propose positioningalgorithms tailored for implementation in these types of networks.In addition to positioning algorithms, we also study algorithmsfor the estimation of distance between network transceivers basedon transmitted wide-band RF signals, and consider the interactionbetween the ranging and the positioning algorithm. In thealgorithm design, we aim for low complexity and robustness againstthe most common types of error sources, including errors caused byblocked (non-line-of-sight) RF channels, and/or multipathpropagation. On a side-track, we study the feasibility ofcharacterizing the surrounding environment in which a wide-bandwireless sensor network is deployed. This characterization is donein terms of the approximate location of reflective objects thatgenerate significant multi-path components and/oramplify-and-forward relays.The second problem we consider is a scheduling problem thatappears not only in wireless sensor networks, but also in otherwireless networks. We propose a relatively simple model forpacket-loss in a Rayleigh fading environment, and use this modelin an attempt to schedule transmissions in the network so as tominimize the average probability of packet-loss. Since wirelesssensor nodes often only have a limited energy source, and packetretransmissions consume energy, this problem is especiallyimportant in the context of wireless sensor networks

Positioning and Tracking in Asynchronous Wireless Sensor Networks

This thesis deals with the problem of locating mobile nodes in anasynchronous wireless communication network, i.e., a wireless network of mobileterminals where some or all nodes do not have access to a global time reference.A strong focus lies on reducing the complexity associated with straight forwardclassical algorithms of node coordinate estimation. The thesis is based on anumber of previously published papers, listed in the introductory chapter.Two complexity reducing data preprocessing methods are presented. Bothpreprocessors achieve a complexity reduction through a cancellation of unknownclock-offsets from the estimation problem. Based on a concept of invariantpreprocessors, we show how the individual unknown clock-offsets at some or allnodes in the network may be discarded from the estimation problem, without anydegradation of the asymptotic performance bounds of the positioning problem.We further present two, fully distributed, sub-optimal positioning algorithmsthat operate on a set of asynchronous delay measurements. The first, called thekernel algorithm, reduces complexity by a divide and conquer approach. Thesecond algorithm is based on a mechanical analogy of the positioning problem. Weevaluate the performance of both algorithms, in terms of the mean-squaredpositioning error, by computer simulation. The performance of the kernelalgorithm is found to lie on the order of the delay measurement accuracy, whilethe second algorithm is shown to attain the Cram\ue9r-Rao lower bound under a setof reasonable assumptions.In the last part of the thesis, a novel tracking filter is proposed to reducethe complexity associated with tracking maneuvering objects in a wirelessnetwork. The tracking filter is based on a classical Kalman filter, but usesadditional information, supplied by the tracked node, to aid in the trackingprocess. One drawback associated with this type of approach to tracking is thepossibility of an unstable filter. We argue that the implementation can be maderobust using very simple alterations. Further, we argue that the classicalmean-squared-error performance measure is not fully appropriate for delaysensitive applications, and introduce a novel performance measure called thetime margin measure, suitable for evaluation of tracking algorithms that operateunder latency constraints. We discuss the merits of our proposed trackingfilter, with respect to this new performance measure, as compared to a classicalKalman implementation