Hassan Naseri

Synchronization and ranging by scheduled broadcasting

In this paper we introduce a novel method for synchronization and range estimation in wireless networks, that can also be applied to other broadcast-based networks. The method is based on broadcasting messages by the nodes in a single neighborhood, and estimating their time of arrival at every node. Timing errors and pairwise distances are estimated simultaneously. The number of messages needed in our method is linear to the number of nodes, versus quadratic for commonly used techniques. The algorithm is analyzed by simulation, showing equal performance compared to the state of the art at significantly lower complexity in communication.

A generalized formulation for harmonic retrieval in correlated noise

In this paper we develop a generalized formulation for harmonic retrieval in correlated noise. Well-known spatial smoothing-based ESPRIT and the Matrix Pencil methods are important special cases of the proposed formulation. The connection between these methods is established analytically. The proposed generalized formulation is applicable to single-snapshot scenarios with arbitrary noise covariance matrix. Moreover, a numerical study is included showing that the Matrix Pencil method is robust to mismodeling of the noise covariance matrix.

Indoor mapping based on time delay estimation in wireless networks

In indoor wireless localization, navigation and communications, knowledge of the floor plan is valuable side information and provides more reliable performance. Such information may not be available. Estimating indoor maps using sensor networks and time delay measurements, i.e., without angular information, is a challenging task. In this paper, a novel algorithm is developed to solve the problem of mapping and measurement clustering. The algorithm is applicable to wireless and acoustic networks with high resolution time delay measurements.

Cooperative joint synchronization and localization using time delay measurements

In this paper a novel algorithm is proposed for joint synchronization and localization in ad hoc networks. The proposed algorithm is based on broadcast messaging, with number of messages linear to the number of nodes, versus quadratic for techniques based on two-way message exchange. The identifiability of network synchronization problem is improved by introducing localization constraints. Hence, the proposed algorithm does not require a full set of measurements. Numerical results are provided using a model based on wireless LAN specifications. In scenarios with missing data, the proposed algorithm significantly improves synchronization and localization performance compared to commonly used techniques.

Multipath-aided cooperative network localization using convex optimization

Determining the location of a mobile device using radio or acoustic signals for distance measurement in the face of multipath propagation is a challenging task. In this paper the problem of multipath-aided cooperative localization is formulated as an optimization problem using a geometric model. Multipath-aided network localization exploits multipath propagation to improve the identifiability and performance of localization. The novel multipath-aided cooperative positioning (macop) algorithm, which uses semidefinite programming relaxation, is proposed to solve this problem. Simulation results show a significant improvement in localization performance compared to existing methods.

Cooperative Simultaneous Localization and Mapping by Exploiting Multipath Propagation

An affordable and reliable indoor positioning is a highly needed service. Moreover, maps of the indoor environment are vital to many applications. In this paper, a method for joint localization and mapping using multipath delay estimates is developed. Required high-resolution estimates of multipath delays may be obtained using radio frequency or acoustic measurements among a set of nodes in a network. In this paper, the problem is modeled in two-dimensional space with arbitrary node configuration and assuming a convex polygonal room shape. Joint localization and mapping is formulated as an optimization problem. It is subdivided and relaxed into two convex subproblems, which can be solved in an alternating manner. A method for data association and a low-complexity mapping algorithm stemming from Hough transform are proposed. Both the estimation performance and identifiability of the indoor localization problem are improved. Moreover, a basic map of the propagation environment is produced.

Indoor mapping using MIMO radio channel measurements

Geometrical maps of the indoor environment are vital to many applications such as indoor localization and robot navigation. In this paper, a method for three-dimensional indoor mapping using multipath delay and direction estimates is developed. Required high-resolution estimates of multipath propagation path parameters are obtained using radio frequency measurements between two antenna arrays at multiple locations. A ray-tracing algorithm is developed for detecting specular propagation paths of radio signals and corresponding reflection points. A novel method is proposed to extract walls and other planar structures from the cloud of reflection points. The empirical results show an improved precision and enhanced geometric information compared to previous experiments.