We tackle the problem of pedestrian indoor navigation with Magneto-Inertial Dead Reckoning technology (MIDR) with the integration of the data provided by a Magneto-Inertial Measurement Unit (MIMU). This method is well-known in the literature and very efficient if the spatial distribution of the magnetic field is nonuniform and the gradient of sufficiently high magnitude. However, the quality of the magnetic information decreases as the pedestrian moves toward a weak magnetic zone. We propose, characterize and test a new correction technique of the MDIR velocity based on the detection of walking steps and dynamical modeling of the walk itself.

The rate of a fingerprinting code is defined as R = (1/N) log2M, where N is the code length and M the number of users. Capacity is the supremum of achievable rates for a given class of collusion attacks. Most fingerprinting codes in current literature are algebraic constructions with high minimum distance. These codes have low rate (relative to capacity) and thus long fingerprints for a given number of users and colluders. However, short fingerprints are valuable in media fingerprinting due to the limited number of robust features available for embedding. This paper proposes a framework to build high-rate fingerprinting codes operating near the fundamental capacity limit by concatenating short, random, and statistically independent subcodes. A practical implementation based on the turbo code construction is presented. Each subcode is decoded by a list Viterbi decoding algorithm, which outputs a list of suspect users. These lists are then processed using a matched filter, which extracts the most suspect user and declares him or her guilty. We provide examples of codes that are short, accommodate millions of users, and withstand (with an error probability of the order of 1%) dozens of colluders against the averaging or interleaving attack followed by additive white Gaussian noise. Our fingerprinting codes operate reliably at rates within 30% to 50% of capacity, which are substantially higher than any other existing code. The decoding complexity is linear in N, or, equivalently, in log M.

Digital fingerprinting aims at protecting multimedia contents from illegal redistribution by embedding imperceptible fingerprints identifying the users. We propose two approaches for building fingerprinting codes that accommodate millions of users and resist tens of colluders. These approaches are based on recent information-theoretic analyses of good fingerprinting codes in two regimes: (1) very low rates, and (2) rates near capacity. Good low-rate codes have high minimum distance. Good high-rate codes are short and random-like. Simulation results are presented to assess decoding performance.