Direction-Of-Arrival (DOA) estimation of acoustic signals is of great interest in various applications including battlefield acoustic and noise localization. Acoustic sensors are employed in an array configuration to estimate DOAs based on the time differences of arrival DOAs. However, the acoustic sensors in the network have all their own Data AcQuisition (DAQ) unit with independent clocks than, it might not be possible to perfectly synchronize the network which affects the performance of the time differences of arrival reliably.

In this thesis we consider the issue of clock synchronization errors in a network where Acoustic Vector Sensors (AVSs) are used. AVSs are shown to be advantageous in terms of direction finding compared to conventional Acoustic Pressure Sensors (APSs) due to their directional particle velocity measurement capability. Initiallity the measurement model for AVSs is presented. After that the behavior of the clocks is incorporated in the measurement model of the full array setup. Subsequently, the effects of the clocks on the MVDR DOA estimation method is discussed.

The model with clock errors is used in the development of three new DOA-estimation methods. The first two techniques are eigenstructure methods that are capable of finding the DOAs regardless of the accuracy of the synchronization. However, to find the DOAs with high accuracy in a real-time application these methods are not due to their high computational cost. Alternatively, the third proposed algorithm takes the DOA estimate from previous methods with low accuracy as its input. The algorithm estimates the DOA in an iterative fashion with high accuracy based on these estimates with low accuracy.

Finally, measurements are conducted in a controlled environment in order to show that these methods are usable in practical situations.

In this thesis five different Direction Of Arrival algorithms will be developed for use with Microflown's Acoustic Vector Sensors, which will determine the direction an acoustic signal originates from. These algorithms will run on a main-station that will remotely receive data from an array of AVSs. The performance of these algorithms is examined using simulations and measurements obtained by a test setup. Finally, it is discussed under what circumstances which algorithm delivers the best performance.