# Compact Bistatic Iterative Passive Radar Based on Terrestrial Digital Video Broadcasting Signals
## 4 Results and Discussion
Although the target and receivers are placed in different positions, no trajectory is obtained, only coordinates are estimated. In this figure, the results of our proposal are shown. Additionally, as in [23], we present the use of several channels transmitted by the same DVB-T emitter in order to improve the results of channel estimation; up to three different channels, which is a common situation in most places, i.e., the reception of at least three channels properly is a setup typical of many applications. Several strategies have been tested, and that in the figures is the optimal approach, involving the coherent incorporation of equal gain combining the pilot signals of all different channels. On this basis, the SNR is improved, and the channel's estimations are also improved. For comparison purposes, the algorithm proposed in [35] was also adapted to this scenario, and the results show that our proposal outperforms it. The SNR is an important variable to take into account in radar systems [36]. The normalized MSE is calculated as follows  
\[MSE=\frac{1}{N}\sum_{n=1}^{N}\sqrt{\left(\frac{\mathbf{x}-\mathbf{\hat{x}_{n} }}{\mathbf{x}}\right)^{2}} \tag{17}\]  
where \(N\) is the total number of simulated samples. As can be seen in Figure 11, the estimation for lower values of SNR is poor. However, once the estimates are within what we could define as the lock-in range of the algorithm, the error is very small because the algorithm will provide a position that is very close to the true value. This lock-in range is the SNR range that allows the estimation of coordinates within a level of accuracy that ensures that the iterative algorithm is able to correct almost completely. The lock-in range is able to support large errors of dozens of meters in estimations. Moreover, since we rely solely on channel estimation to determine the time of arrival, and thus the distance, the crucial factor is the delay of the taps, rather than their amplitude. Figure 11: Normalized MSE. The proposal in [23] is labeled as [PERSON] et al.’20 for comparison purposes. These two aspects enhance the robustness of our proposal, ensuring good performance even when the receiver has a low SNR. In Figure 11, we present curves for using two and three different channels simultaneously. As shown, the benefits of using several channels are a couple of dB in the working range. For comparison purposes, the proposal in [35] (which we adapted to this scenario) is included in the figure. Since the proposal in [35] deals with the estimation of the trajectory using several (up to six) different transmitters and applying the Kalman filter to the signal received from the different transmitters, we made the following modifications to adapt it to our scenario. First, a single transmitter is used; however, we utilize three different signals coming from the three frequency channels used by the transmitter, i.e., we have three signals from the transmitter. Moreover, we do not estimate speed, and the simulation has a short enough duration to guarantee that the target may be considered static. It is clear that our proposal outperforms the alternative once the SNR is higher than \(-6\) dB.