System identification techniques are routinely used in experimental stability and control studies throughout the aerospace industry. Over the years, various researchers at the College of Aeronautics have contributed to this field; most recently some of the latest methods have been employed to estimate the stability and control derivatives of a variety of aircraft types. Although the more recent investigations provide a useful insight into the capabilities and characteristics of several up-to-date methods, they have not resulted in tools which may be used on a routine basis. Consequently, the purpose of this report is to describe a set of procedures which are straightforward to apply, and produce reasonable solutions to the type of linear parameter identification problems which are often found in aerospace work. Recordings of the short period and phugoid modes from Handley-Page Jetstream G-NFLC are used throughout as examples. Firstly, those characteristics of the aircraft’s instrumentation system which influence the quality of the signals - sample rate, antialiasing filters, time delays - are considered. This information is used in conjunction with standard signal processing techniques to ensure that the data is of sufficient quality to be used in the parameter estimation process. Next, a basic Fourier analysis and a least squares algorithm are employed to produce non- parametric and parametric models respectively. The results thus obtained are comparable to those generated using more sophisticated techniques. In conclusion, standard signal processing methods combined with relatively simple estimation theory offer an adequate solution to the linear parameter estimation problem.Cranfield University