A single--path--oriented fault--effect propagation in digital circuits considering multiple--path sensitization

Various satisfiability problems in combinational logic blocks as, for example, test pattern generation, verification, and netlist optimization, can be solved efficiently by exploiting the fundamental concepts of propagation and justification. Therefore, fault effect propagation gains further importance. For the first time, we provide the theoretical background for a single path oriented fault effect propagationconsidering both single and multiple path sensitization. We call this approach SPOP. Furthermore, we formulate necessary and sufficient sensitization conditions for SPOP. From these conditions the best suited algebra for propagation can be derived. Experimental results for stuck–at test pattern generation demonstrate that the new approach is orthogonal to D–frontier based methods. We achieve substantial improvements with respect to test pattern generation time and quality.

Ionospheric Scintillation Mitigation With Kalman PLLs Employing Radial Basis Function Networks

We investigate two adaptive Kalman phase-locked loop (PLL) structures for ionospheric scintillation mitigation for global navigation satellite systems receivers, employing radial basis function (RBF) networks to model the scintillation phase and amplitude, instead of the typically employed autoregressive (AR) models. In the first structure, the Kalman filter innovations are computed by the arctangent phase discriminator, and the state estimates are directly employed in the carrier replica generation. In the second structure, the Kalman filter measurements are the prompt correlator outputs, and the error states are computed and used by a state feedback controller to provide a control signal to drive the carrier replica generation. The nonlinear RBFs provide more flexibility to capture nonlinear dynamics evolving with time, possibly present in the scintillation phase and amplitude. The weights of the RBF networks and the covariance matrices of the process and measurement noise of the Kalman filters are estimated online in the adaptive Kalman PLL structures. Simulations with synthetic severe scintillation data show the capability of the proposed Kalman PLLs to improve robustness to scintillation effects in carrier synchronization, with performance similar to the corresponding structures employing AR scintillation models. Simulations using recorded scintillation data collected by a commercial receiver highlight the learning and generalization capability of the RBF networks to cope with evolving scintillation characteristics over time with possibly nonlinear effects. The Kalman PLL structures employing the RBF networks present reduced errors compared with the structures using AR models

Linear time-invariant filtering for real-time monitoring of ionospheric scintillation in GNSS receivers

We propose an algorithm for estimating the ionospheric scintillation phase on global navigation satellite systems (GNSS) receivers for scintillation monitoring. The algorithm comprises linear time-invariant filtering of available observables or easily derived in traditional or Kalman filter-based carrier tracking loop structures, exploiting their complementary frequency content to provide real-time scintillation phase estimates for monitoring purposes. This algorithm is developed for receivers with traditional and Kalman frequency locked loops, but can be adapted to receivers with traditional and Kalman phase locked loops. The performance of the algorithm is evaluated via simulations with synthetic severe scintillation data, showing its capability to provide the scintillation phase estimates. In addition, we evaluated the algorithm with real data presenting equatorial scintillation collected by a professional GNSS receiver, where the scintillation phase standard deviation computed from the estimates provided by the real-time algorithm is compared to the standard deviation derived by post-processing, showing good agreement