Large ν\nu-νˉ\bar{\nu} Oscillations from High-Dimensional Lepton Number Violating Operator

It is usually believed that the observation of the neutrino-antineutrino (${\nu}$-$\bar{\nu}$) oscillations is almost impossible since the oscillation probabilities are expected to be greatly suppressed by the square of tiny ratio of neutrino masses to energies. Such an argument is applicable to most models for neutrino mass generation based on the Weinberg operator, including the seesaw models. However, in the present paper, we shall give a counterexample to this argument, and show that large $\nu$-$\bar{\nu}$ oscillation probabilities can be obtained in a class of models in which both neutrino masses and neutrinoless double beta ($0\nu\beta\beta$) decays are induced by the high-dimensional lepton number violating operator ${\cal O}_7 = \bar{u}_R l^c_R \bar{L}_L H^*d_R + {\rm H.c.}$ with $u$ and $d$ representing the first two generations of quarks. In particular, we find that the predicted $0\nu\beta\beta$ decay rates have already placed interesting constraints on the $\nu_e \leftrightarrow \bar{\nu}_e$ oscillation. Moreover, we provide an UV-complete model to realize this scenario, in which a dark matter candidate naturally appears due to the new $U(1)_d$ symmetry.Comment: 21 pages, 6 figure

Codes Cross-Correlation Impact on S-curve Bias and Data-Pilot Code Pairs Optimization for CBOC Signals

The aim of this paper is to analyze the impact of spreading codes cross-correlation on code tracking performance, and to optimize the data-pilot code pairs of Galileo E1 Open Service (OS) Composite Binary Offset Carrier (CBOC) signals. The distortion of the discriminator function (i.e., S-curve), due to data and pilot spreading codes cross-correlation properties, is evaluated when only the data or pilot components of CBOC signals are tracked, considering the features of the modulation schemes. Analyses show that the S-curve bias also depends on the receiver configuration (e.g., the tracking algorithm and correlator spacing). In this paper, two methods are proposed to optimize the data-pilot code pairs of Galileo E1 OS. The optimization goal is to obtain minimum average S-curve biases when tracking only the pilot components of CBOC signals for the specific correlator spacing. The S-curve biases after optimization processes are analyzed and compared with the un-optimized results. It is shown that the optimized data-pilot code pairs could significantly mitigate the intra-channel (i.e., data and pilot) codes cross-correlation，and then improve the code tracking performance of CBOC signals

Joint Probabilistic Data Association-Feedback Particle Filter for Multiple Target Tracking Applications

This paper introduces a novel feedback-control based particle filter for the solution of the filtering problem with data association uncertainty. The particle filter is referred to as the joint probabilistic data association-feedback particle filter (JPDA-FPF). The JPDA-FPF is based on the feedback particle filter introduced in our earlier papers. The remarkable conclusion of our paper is that the JPDA-FPF algorithm retains the innovation error-based feedback structure of the feedback particle filter, even with data association uncertainty in the general nonlinear case. The theoretical results are illustrated with the aid of two numerical example problems drawn from multiple target tracking applications.Comment: In Proc. of the 2012 American Control Conferenc