A study of data analysis techniques for the multi-needle Langmuir probe

Abstract

In this paper we evaluate two data analysis techniques for the multi-needle Langmuir probe (m-NLP). The instrument uses several cylindrical Langmuir probes, which are positively biased with respect to the plasma potential in order to operate in the electron saturation region. Since the currents collected by these probes can be sampled at kilohertz rates, the instrument is capable of resolving the ionospheric plasma structure down to the meter scale. The two data analysis techniques, a linear fit and a non-linear least squares fit, are discussed in detail using data from the Investigation of Cusp Irregularities 2 sounding rocket. It is shown that each technique has pros and cons with respect to the m-NLP implementation. Even though the linear fitting technique seems to be better than measurements from incoherent scatter radar and in situ instruments, m-NLPs can be longer and can be cleaned during operation to improve instrument performance. The non-linear least squares fitting technique would be more reliable provided that a higher number of probes are deployed.