Empirical Success Rate Research Articles

Role of stochastic model on GPS integer ambiguity resolution success rate

An important step in the high-precision GPS positioning is double-difference integer ambiguity resolution (IAR). The fraction or percentage of success among a number of integer ambiguity fixing is called the success rate. We investigate the ambiguity resolution success rate for the GPS observations for two cases, namely a nominal and a realistic stochastic model of the GPS observables. In principle, one would expect to have higher reliability on IAR success rates if a realistic GPS observables stochastic model is employed. The GPS geometry-based observation model is employed in which a more realistic stochastic model of GPS observables is determined using the least-squares variance component estimation. Two short and one GPS long baseline datasets and one simulated dataset are employed to evaluate the efficacy of the proposed algorithm. The results confirm that a more realistic stochastic model can significantly improve the IAR success rate on individual frequencies, either on L1 or on L2. An improvement of 25 % was achieved to the empirical success rate results. The results are of interest for many applications in which single-frequency observations can be used. This includes applications like attitude determination using single frequency single epoch of GPS observations.

A Logic-Based Approach to Problems in Pragmatics

A Logic-Based Approach to Problems in Pragmatics After an exposé of the programme involved, it is shown that the Gricean maxims fail to do their job in so far as they are meant to account for the well-known problem of natural intuitions of logical entailment that deviate from standard modern logic. It is argued that there is no reason why natural logical and ontological intuitions should conform to standard logic, because standard logic is based on mathematics while natural logical and ontological intuitions derive from a cognitive system in people's minds (supported by their brain structures). A proposal is then put forward to try a totally different strategy, via (a) a grammatical reduction of surface sentences to their logico-semantic form and (b) via logic itself, in particular the notion of natural logic, based on a natural ontology and a natural set theory. Since any logical system is fully defined by (a) its ontology and its overarching notions and axioms regarding truth, (b) the meanings of its operators, and (c) the ranges of its variables, logical systems can be devised that deviate from modern logic in any or all of the above respects, as long as they remain consistent. This allows one, as an empirical enterprise, to devise a natural logic, which is as sound as standard logic but corresponds better with natural intuitions. It is hypothesised that at least two varieties of natural logic must be assumed in order to account for natural logical and ontological intuitions, since culture and scholastic education have elevated modern societies to a higher level of functionality and refinement. These two systems correspond, with corrections and additions, to Hamilton's 19th-century logic and to the classic Square of Opposition, respectively. Finally, an evaluation is presented, comparing the empirical success rates of the systems envisaged.

Multirate Synchronous Sampling of Sparse Multiband Signals

Recent advances in electro-optical systems make them ideal for undersampling multiband signals with very high carrier frequencies. In this paper, we propose a new scheme for sampling and reconstructing of a multiband sparse signals that occupy a small part of a given broad frequency range under the constraint of a small number of sampling channels. The locations of the signal bands are not known <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> . The scheme, which we call synchronous multirate sampling (SMRS), entails gathering samples synchronously at few different rates whose sum is significantly lower than the Nyquist sampling rate. The signals are reconstructed by finding a solution of an underdetermined system of linear equations by applying a pursuit algorithm and assuming that the solution is composed of a minimum number of bands. The empirical reconstruction success rate is higher than obtained using previously published multicoset scheme when the number of sampling channels is small and the conditions for a perfect reconstruction in the multicoset scheme are not fulfilled. The practical sampling system which is simulated in our work consists of three sampling channels. Our simulation results show that a very high empirical success rate is obtained when the total sampling rate is five times higher than the total signal support of a complex signal with four bands. By comparison, a multicoset sampling scheme obtains a very high empirical success rate with a total sampling rate which is three times higher than the total signal support. However, the multicoset scheme requires 14 channels.