Research Of SNR Estimation Algorithm In Spread Spectrum Measurement And Control Receiver

SNR(Signal to Noise Radio) estimation is of great significance in design, simulation and practical application of a digital receiver system. In the receiver design and simulation phase, studying various aspects of receiver performance is inseparable from an accurate estimate of signal to noise ratio in the receiver channel. In the practical application of spread spectrum measurement and control communication systems, SNR estimation as the characterization parameters for communication channel, it is very important significance for assisted completing the electronic countermeasure and synchronization capture in the spread spectrum communication process.In this article, the principles and characteristics of recent representative SNR estimation algorithms under AWGN channels are discussed and presented, including ML (Maximum Likelihood) algorithm, SVD (Autocorrelation Matrix Singular Value Decomposition) algorithm, M2M4 (Second-and-Fourth order Moment) algorithm in time-domain, and Spectral Estimation algorithm in frequency-domain. These four methods were studied in this paper, as the theoretical basis and methods of thinking for the SNR estimation in the spread spectrum communications systems.According to the characteristics of low SNR in spread spectrum communication system, based on several existing SNR algorithms, several good SNR estimation methods are proposed, they are SNR estimation algorithm based on curve fitting, SNR estimation algorithm based on high-order cumulant, SNR estimation algorithm based on signal envelope. They are non-data-aided real time SNR estimator and is shown to have the following advantages: (1) it does not require prior carrier synchronization; (2) accurate estimates can be generated in real time; (3) it has a compact fixed-point hardware implementation suitable for field-programmable gate arrays and application-specific integrated circuites.The SNR estimators are investigated by the computer simulation of baseband quadrature phase-Shift Keying(QPSK) signals in complex additive white Gaussian noise (AWGN). The mean square error and the mean estimation is used as measure of performance. And the simulated performance are compared to a published Cramer-Rao bound (CRB) for complex AWGN that is derived here. By performance analysis, taking into account the method of implementation hardware complexity, we select the based on the signal envelope of the SNR estimation method as the method used by the system and implement in the FPGA.