In this paper, a cascaded form sparse finite impulse response (FIR) filter design algorithm is proposed. By decomposing a filter into two subfilters, the sparse filter design problem is reformulated as a quadratic constrained {l} -{0}-norm minimization problem, which is further transformed to a convex problem through the introduction of a binary masking vector. An iterative forth-And-back search with sequence direction and error direction control is proposed to optimize the binary masking vector by minimizing the distance between the minimax approximation error and the specified upper bound. Experimental results show that the proposed design algorithm can improve the sparsity with comparable or even lower effective filter order.