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Global network of advanced Interferometric gravitational wave (GW) detectorsare expected to be on-line soon. Coherent observation of GW from a distantcompact binary coalescence (CBC) with a network of interferometers located indifferent continents give crucial information about the source such as sourcelocation and polarization information. In this paper we compare differentmulti-detector network detection statistics for CBC search. In maximumlikelihood ratio (MLR) based detection approaches, the likelihood ratio isoptimized to obtain the best model parameters and the best likelihood ratiovalue is used as statistic to make decision on the presence of signal. However,an alternative Bayesian approach involves marginalization of the likelihoodratio over the parameters to obtain the average likelihood ratio. We obtain ananalytical expression for the Bayesian statistic using the two effectivesynthetic data streams for targeted search of non-spinning compact binarysystems with an uninformative prior on the parameters. Simulations are carriedout for testing the validity of the approximation and comparing the detectionperformance with the maximum likelihood ratio based statistics. We observe thatthe MLR {\it hybrid} statistic gives comparable or better performance withrespect to the Bayesian statistic.

Performance comparison of multi-detector detection statistics in targeted compact binary coalescence GW search