In ultra-wideband (UWB) communication systems with impulse radio (IR) modulation, the bandwidth is usually 1GHz or more. To process the received signal digitally, high sampling rate analog-digital-converters (ADC) are required. Due to the high complexity and large power consumption, employing multibit high-rate ADC is impractical. However, monobit ADC is appropriate. The optimal monobit digital receiver has already been proposed. This kind of receiver has been derived under the assumption that the intersymbol interference (ISI) either does not exist or can be regarded as random noises. When encountered with heavy ISI, these receivers are not excellent as we expected. There are many approaches to solve the ISI problem in regular communication systems. When applied to monobit systems, unfortunately, most of them turned out to be unavailable due to the great loss of quantification. Decision feedback equalization (DFE) is an effect way to deal with ISI in monobit digital systems. In this paper, we propose an algorithm that combines Viterbi decoding and DFE together for monobit receivers. In this way, we suppress the impact of ISI effectively, thus improving the bit error rate (BER) performance. In addition, we introduce a method called state expansion by which better BER performance can be achieved. Under the condition of perfect channel state information(PCSI), the simulation results show that the algorithm has about 1dB SNR gain compared to separate monobit BPSK demodulation with convolutional decoding and 1dB SNR loss compared to the BER performance of optimal monobit receiver in the channel without ISI. Compared to the full resolution detection in fading channel without ISI, it has 3dB SNR loss after state expansion. Under the CSI that achieved from iterative evaluation, both the performance of optimal monobit receiver and joint receiver have 1dB loss compared to that of PCSI.