This paper presents a new proportionate normalized subband adaptive filter (PNSAF) algorithm, called the IAF-PNSAF, which assigns an individual activation factor for each filter coefficient instead of a common one for all filter coefficients as in the standard PNSAF algorithm. This algorithm achieves an improved performance in terms of the convergence rate and tracking capability for identifying a highly sparse system. Moreover, to overcome the trade-off of the fixed-step-size IAF-PNSAF algorithm between the fast convergence rate and small steady-state misalignment, its adaptive combination version is proposed. Simulation results for identifying the impulse response with high sparseness have demonstrated that the proposed algorithms outperform their counterparts.