## 3 Multipath Interference Suppression
In order to evaluate the target sensing performance of forward scatter echo signal for different false alarm probabilities, the parameters are set as follows: the sampling frequency is \(f_{s}=10.23\) MHz, the sampling points is \(2\times 10^{7}\), the GPS direct wave power is \(P_{d}=-100\) dBm, the symbol rate is \(f_{Gb}=1.023\) MHz, the carrier frequency is \(f_{c}=1.57\) GHz, the aerial target flight altitude is 10 km, the flight speed is 100 m/s, the average power of the echo signal is \(P_{r}=-135\) dBm; 2000 Monte Carlo simulation results are used. It can be seen in Figure 13 that, as the false alarm probability increases, so does the target sensing performance under the same conditions. When the false alarm probability is \(10^{-4}\), the sensing performance can reach 100% with SNR = \(-37\) dB, and when the false alarm probability is \(10^{-5}\), the sensing performance under SNR = \(-35\) dB can reach 100%,

Figure 12: Sensing performance with different sampling points. and when the false alarm probability is \(10^{-6}\), the sensing performance can reach 100% with SNR = \(-34\) dB. Next, we compare the target sensing performance of the proposed method with these of [32; 33]. The parameters are set as follows: the sampling frequency is \(f_{s}=10.23\) MHz, the sampling points is \(2\times 10^{7}\), the false alarm probability is \(P_{fa}=10^{-4}\), the GPS direct wave power is \(P_{d}=-100\) dBm, the symbol rate is \(f_{Gb}=1.023\) MHz, the carrier frequency is \(f_{c}=1.57\) GHz, the aerial target flight altitude is 10 km, the flight speed is 100 m/s, the average power of the echo signal is \(P_{r}=-135\) dBm; 2000 Monte Carlo simulations are used. As can be seen from Figure 14, the sensing performance of the proposed method is better than [32; 33]. This is because the proposed method based on LCT has a good interference suppression effect; therefore, under the same conditions, the detection amount of the proposed method is more conducive to the detection of target echoes, which is superior to the method proposed in [32]. The method proposed in [33] is based on the shadow area in the case of forward scattering, but as the height of the target increases, its attenuation at the baseline decreases, which is not conducive to target detection. The computational complexity of the proposed method is \(O(NM\cdot n_{lct})\), and the computational complexity of [32] method is \(O(Nm)\), and the computational complexity of [33] method is \(O(N\text{log}_{2}N)\), where \(N\) denotes the number of signal sampling points, \(M\) stands for the number of sampling points in the linear canonical domain, and \(n_{lct}\) and \(m\) are the number of searches. Overall, although the computational complexity of the proposed method is higher than [32; 33], the proposed method has better target sensing performance and multipath interference suppression effect. In order to evaluate the target parameter estimation performance of the proposed method, the parameters are set as follows: the sampling frequency is \(f_{s}=10.23\) MHz, the sampling points is \(3\times 10^{7}\), the GPS direct wave power is \(P_{d}=-100\) dBm, the symbol rate is \(f_{Gb}=1.023\) MHz, the carrier frequency is \(f_{c}=1.57\) GHz, the target flight altitude is 8 km, the flight speed is 125 m/s, the average power of the echo signal is \(P_{r}=-135\) dBm; 2000 Monte Carlo simulation results are used. As can be seen from Figure 15, both the proposed LCT+MF method and the proposed MF+LCT method in this paper can achieve good estimation performance for the target flight altitude, and they improve as the signal-to-noise ratio (SNR) increases. This is because the increase in the SNR makes the corresponding peaks during parameter estimation more

Figure 13: Sensing performance with different false alarm probabilities. prominent, thereby improving the parameter estimation performance.