Novel Dictionary Decomposition to Acquire GPS Signals Using Compressed Sensing

When acquiring any wireless signal such as GPS, there is a strong association between the amount of integration, correlation or matching performed by the receiver with the strength of the signal, depending on the acquisition technique used. The Compressive Sensing technique (CS) does reduce the computation by up to 60% over correlators based method, yet still maintains acquisition integrity. This paper proposes a new method for implementing the dictionary matrix required for CS and achieving a further saving of more than 80% in the signal acquisition process without loss of the integration between the code and frequency irrespective of the signal strength. This is achieved by removing the generated Doppler shifts from the “overcomplete” dictionary matrix, while keeping the carrier frequency fixed for all these generated shifted SV codes. Our MATLAB simulation for various signal condition scenarios proves that up to 90% of computational complexity and memory space can saved