A Novel Method To Extend Coherent Integration for Weak GPS Signal Acquisition

Abstract

In order to enhance the sensitivity of Global Positioning System (GPS) receivers, increasing the coherent integration time in acquisition process is necessary. This letter analyses the limitation to coherent integration in acquisition algorithms due to the bit sign transition of navigation data and proposes a novel time parallel acquisition algorithm with transition detection (denoted as TPATD) to overcome the bit sign transition limitation. Fast Fourier transform (FFT) operation is applied to the proposed TPATD algorithm to search the code delay in parallel. Meanwhile, the algorithm extends the coherent integration time to one entire navigation data bit duration. Simulation results demonstrate the effectiveness of the proposed algorithm. The receiver operating characteristic (ROC) curves show that TPATD algorithm outperforms the existing acquisition techniques.

An Acquisition Scheme Based on a Matched Filter for Novel Communication and Navigation Fusion Signals

“…At the same time, the receiver cannot simultaneously demodulate the OFDM signals transmitted by three or more MDBBSs, so we can only use the added navigation system to achieve the CMMB positioning. Thanks to PRN sequence orthogonality, incoming signal of all received MDBBSs can be analyzed separately [ 21 ]. The digital broadcasting signal is received by RF antenna, and the output of RF antenna is written as: where, N is the sum of the received signals that are sent by N different MDBBSs, A i is the signal amplitude, τ i is the incoming code delay, f d,i is the incoming Doppler shift, stands for the additive Gaussian white noise (AWGN) component with zero mean ( μ = 0) and variance ( ).…”

A Pseudorange Measurement Scheme Based on Snapshot for Base Station Positioning Receivers

“…Thanks to the orthogonality of pseudo codes, the received signals from base stations can be analyzed separately [19]. The fusion signal is received by radio frequency (RF) antenna of the receivers, and the output of RF antenna is expressed as:$rfalse(tfalse)=true\sum _{i=1}^N{A}^{false(ifalse)}{s}^{false(ifalse)}false(t-{\tau }_{i}false)\cos false(2\pi false(f_c+f_{d,i}false)t+{\phi }_{0,i}false(tfalse)false)+\omega false(tfalse)$ where N is the number of the received signals from N different base stations, $A^{false(ifalse)}$ is the signal amplitude, ${\tau }_i$ is the incoming signal delay, $f_{d,i}$ is the incoming Doppler shift, $\omega false(tfalse)$ stands for the additive Gaussian white noise (AWGN) component with zero mean ($\mu =0$) and variance (${\sigma }_n^2$).…”

Intelligent Multisensor Cooperative Localization Under Cooperative Redundancy Validation

“…An important property of IoT is the location of the Things, such as applications for the pedestrian/vehicle navigation, logistics management, industrial equipment monitoring and venue supervision [1]- [6]. The Global Positioning System (GPS) itself is not enough in IoT applications because in these complicated environments (such as the urban areas and the buildings), the satellite signal can be blocked sometimes that might lead to very large errors or even localization suspend [7], [8]. Thus, different types of localization systems or methods are developed to overcome the weaknesses of satellite positioning system, such as using Wireless Sensor Network (WSN) [6], [9]- [14], base-station [15]- [19], Wi-Fi/Bluetooth [1], [2], [20]- [22] and ultra-wide bandwidth (UWB) signal [3], [22]- [26].…”