| Summary: | Approved for public release; distribution is unlimited === Wireless communication technology has become a critical aspect in many civilian and military applications. With regard to remote sensing, search and rescue, disaster relief operations and signals intelligence, there exists an interest in developing capabilities to collect these signals-of-interest. The objective of this dissertation is to maximize signal collection performance in the presence of signal measurement and sensor related errors. To accomplish this objective, we proposed a signal collection scheme that exploits an elevated, mobile network to maximize the collaborative collection of a target signal. The proposed scheme begins with source localization. This technique consists of an initial weighted least-squares estimate followed by a maximum-likelihood estimate. Implemented on an elevated, mobile network, this technique is able to obtain an optimal localization. To enhance localization robustness, we developed an outlier rejection process that mitigates the effects of measurement and sensor position errors. To collect the signal, this research quantified the effects of sensor position errors on beamforming and proposed a novel signal collection scheme that combines signal estimation and collaborative beamforming. Using all these techniques in concert, we were able to show that the proposed scheme outperforms standard collaborative beamforming in the presence of sensor position errors.
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