  The TileCal is the main hadronic calorimeter of ATLAS and it covers the
central part of the detector ($|\eta|$ < 1.6). The energy deposited by the
particles in TileCal is read out by approximately 10,000 channels. The signal
provided by the readout electronics for each channel is digitized at 40 MHz and
its amplitude is estimated by an optimal filtering algorithm. The increase of
LHC luminosity leads to signal pile-up that deforms the signal of interest and
compromises the amplitude estimation performance. This work presents the
proposed algorithm for energy estimation during LHC Run 2. The method is based
on the same approach used during LHC Run 1, namely the Optimal Filter. The only
difference is that the signal baseline (pedestal) will be subtracted from the
received digitized samples, while in Run 1 this quantity was estimated on an
event-by-event basis. The pedestal value is estimated through special
calibration runs and it is stored in a data base for online and offline usage.
Additionally, the background covariance matrix will also be used for the
computation of the Optimal Filter weights for high occupancy channels. The use
of such information reduces the bias and uncertainties introduced by signal
pile-up. The performance of the Optimal Filter version used in Run 1 and Run 2
is compared using Monte Carlo data. The efficiency achieved by the methods is
shown in terms of error estimation, when different conditions of luminosity and
occupancy are considered. Concerning future work, a new method based on linear
signal deconvolution has been recently proposed and it is under validation. It
could be used for Run 2 offline energy reconstruction and future upgrades.
