The experimental paradigm of one ion packet release per spectrum severely hinders throughput in broadband ion mobility spectrometry (IMS) systems (e.g., drift tube and traveling wave systems). Ion trapping marginally mitigates this problem, but the duty cycle deficit is amplified when moving to high resolution, long pathlength systems. As a consequence, new multiplexing strategies that maximize throughput while preserving peak fidelity are essential for high-resolution IMS separations [e.g., structures for lossless ion manipulations (SLIMs) and multi-pass technologies]. Currently, broadly applicable deconvolution strategies for Hadamard-based ion multiplexing are limited to a narrow range of modulation sequences and do not fully maximize the ion signal generated during separation across an extended path length. Compared to prior Hadamard deconvolution errors that rely upon peak picking or discrete error classification, the masked deconvolution matrix technique exploits the knowledge that Hadamard transform artifacts are reflected about the central, primary signal [i.e., the true arrival time distribution (ATD)]. By randomly inducing mathematical artifacts, it is possible to identify spectral artifacts simply by their high degree of variability relative to the core ATD. It is important to note that the deweighting approach using the masked deconvolution matrix does not make any assumptions about the underlying transform and is applicable to any multiplexing strategy employing binary sequences. In addition to demonstrating a 100-fold increase in the total number of ions detected, the effective deconvolution of data from 5, 6, 7, and 8-bit pseudo-random sequences expands the utility and efficiency of the SLIM platform.