## 1 Introduction  
The state of the Earth's magnetosphere is monitored by INTERMAGNET observatories, which measure the components and total intensity of the geomagnetic field with a discrete-time sampling. Magnetic observatories are equipped with appropriate vector and scalar magnetometers and measure magnetograms in a given standard [1]. To date, there are 153 INTERMAGNET observatories in operation, located on all continents; INTERMAGNET magnetograms are hosted in a public database [2].  
Geomagnetic disturbances arise due to the effects of plasma formations from solar coronal mass ejections on the Earth's magnetosphere. A geomagnetic storm is generally an extreme phenomenon--a sporadic disturbance in the Earth's magnetic field with high amplitudes (500-5000 nT). Sudden commencements (SC) of geomagnetic storms [3] are positive or negative jumps of the geomagnetic field, synchronously observed in almost all observatories. SC are a consequence of the impact of coronal mass ejecta on the Earth's magnetosphere. Typical SC signals are the patterns characterized by an abrupt increase and decrease in the geomagnetic field intensity, which correspond to large values of derivatives. The duration of SC events ranges from minutes to tens of minutes, and the amplitudes of the jumps take on the values of units of percent from the mean level of the geomagnetic field intensity prior to SC; as a rule, SC are surrounded by noise-like geomagnetic field disturbances.  
The main particularity of SC signals is in their occurrence prior to the moment of a geomagnetic storm onset. Calculating the estimates of SC signals as derivatives of the geomagnetic field is a completely natural approach to solving the problem of predicting the occurrence of a geomagnetic storm [3, 4]. Reliable SC recognition is an urgent scientific and technical problem in the subject area of geomagnetism and solar-terrestrial physics.  
A number of publications offer approaches to SC recognition with different efficiencies. For example, some publications [4, 5, 6] describe automated SC recognition techniques using [PERSON]'s wavelets. In [7], it is recommended to use the actual SC characteristics, including amplitude, rise time, and maximum value of the derivative of SC signals. The authors in [8]describe the morphological elements of SC signals, on the basis of which the SC recognition system is built. In [9], the connection between SC events and space weather is discussed. The SC recognition method proposed in this study is aimed at supplementing the existing approaches. The proposed approach to solving the formulated problem of SC recognition consists of using differentiating filters for geomagnetic data. High-pass filtering using differentiating finite impulse response (FIR) filters is applied to clearly separate the SC signal. The structure of such filters is selected based on the problem of optimal use of data from a set of magnetic observatories for a certain time interval.  
In Figure 1, an example of SC between 18:30 and 20:00 UTC is shown based on one-minute-averaged data of components \(H_{x}\), \(H_{y}\), \(H_{z}\) and the total intensity \(H_{0}\) of the geomagnetic field, registered at the ASP magnetic observatory (Alice Springs, Australia) on 22.06.2015 from 00:00 to 23:59. The 1440 values are in nT, \(i=1,\ldots,N_{0}\), \(N_{0}=1440\).  
Similar geomagnetic field jumps followed by the mentioned increase in noise at 18:30-20:00 UTC were registered by all INTERMAGNET observatories.