In bistatic radar, it is important to suppress the undesired signals such as the direct propagated signal from transmitter and its multipath components. Conventionally, some suppression methods have been proposed. They are categorized into the method using a feedback system and the method which subtracts the replicas of the undesired signals. The former method may have the problem on the convergence of the suppression performance. The latter method requires the precise delay times of the undesired signals. In this paper we propose a new method to detect the target in digital terrestrial TV-based bistatic radar which is based on orthogonal frequency division multiplexing (OFDM), without any information on the undesired signals' delay times. In the proposed method, we adapt a scheme based on maximum signal to noise ratio (MSN) algorithm, which makes signal to interference plus noise ratio (SINR) maximum for the desired signal component. The maximum sensitivity is steered so as to match the path that exhibits the delay which relates to the target position, as if the search beam is steered along the direction in array signal processing. In the proposed method, “nulls” are also formed for other delay components to be suppressed simultaneously. In the frequency domain, the carrier components of the scattered signal divided by those of the reference signal indicate the delays caused by scattering. We call these divided carrier components “normalized received signal.” The steered sensitivity and nulls are created by the weight which is applied to the normalized received signal in the frequency domain. We obtain the method to estimate the weight to achieve the maximum SINR in the delay estimation which also includes the compensation for the reduction of the weight's length caused by decorrelation among the delay components. The simulation results show that our proposed method without any information on the undesired signal's delays provides sufficient detection performance for the typical target compared to the conventional one.