A least-squares based method for noisy autoregressive signals has been deve
loped recently, which needs to neither prefilter noisy data nor perform par
ameter extraction. In this brief, a more computationally efficient procedur
e for estimating the measurement noise variance is developed, and then an e
fficient implementation of the method is presented. It is shown that this b
etter way of implementation can considerably reduce the computational requi
rement of the least-squares based method without any performance degradatio
n. Computer simulations that support the theoretical findings are given.