Solar radiation measurements as most time-series data suffer from interruptions. Gaps may occur due to loss of power, misalignment, failure of instruments, insufficient cleaning or other reasons. Quality check procedures identify such malfunctioning and mark untrustworthy data by flags. Even well maintained stations with good equipment usually show gaps. In the case of the Indian SRRA network with its 51 stations operating since 2011, typically around 7% of the data are flagged as potentially erroneous or missing. Duration of gaps ranges from few minutes to several days. However many applications such as solar energy performance simulations need continuous time-series. Therefore it is required to fill the measurement gaps with reasonable data. Depending on duration and type of missing parameters various procedures can be used to fill gaps. This paper describes a set of procedures called ‘basic gap filling’ for solar irradiance, which can be applied without having available additional data. From the over-determined set of global, diffuse and direct radiation a single missing parameter can be calculated from the other two. When two or more solar irradiance components are missing for short gaps, clearness indices are derived to calculate the missing irradiance components. Basic gap filling procedure is applied as part of the SRRA/SolMap projects. The accuracy of the applied basic gap filling methodology is tested and the results show a mean bias of ca. 3 % over GHI, DNI and DHI over all types of gaps.