Pseudonoise (PN) regenerative ranging on-board acquisition performance is assessed in terms of the acquisition time for a given probability of acquisition at a reference signal-to-noise ratio (SNR). So far the detection of the correct ranging code phase alignment has been analyzed by a maximum likelihood (ML) estimation with no amplitude quantization at the chip matched filter output. Despite its optimality in an additive white Gaussian noise (AWGN) channel, an ML estimation finds a maximum value also when no ranging signal (i.e., noise-only) is present at the receiver input thus resulting in a false alarm (FA) detection. On the contrary a suboptimum threshold comparison estimation of the correct ranging code phase alignment can overcome such a hindrance. This work reports the on-board PN regenerative ranging acquisition performance based on threshold comparison with 3-bits soft-quantized correlators along with the relevant trade-offs with respect to the ML estimation.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE :Challenges Facing PFC of a Single-Phase On-Board Charger for Electric Vehicles Based on a Current Source Active Rectifier Input StageABSTRACT:This paper aims to study the facility factor (PF) correction scheme for
PROJECT TITLE :Single-Phase On-Board Integrated Battery Chargers for EVs Based on Multiphase MachinesABSTRACT:The paper considers integration of multiphase (more than three phases) machines and converters into one-phase charging
PROJECT TITLE :Single-Phase On-Board Bidirectional PEV Charger for V2G Reactive Power OperationABSTRACT:This paper presents the look and implementation of a single-part on-board bidirectional plug-in electric vehicle (PEV) charger
PROJECT TITLE : Network Resource Allocation for Users With Multiple Connections Fairness and Stability - 2014 ABSTRACT: This paper studies network resource allocation between users that manage multiple connections, possibly
PROJECT TITLE : Multi-Core Embedded Wireless Sensor Networks Architecture and Applications - 2014 ABSTRACT: Technological advancements in the silicon industry, as predicted by Moore's law, have enabled integration of billions

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry