Frequency-modulated continuous-wave (FMCW) light detection and ranging (LiDAR) is a high-precision ranging and imaging system that has been widely used in various areas, such as self-driving vehicles and industrial inspection. However, during detection, the system is susceptible to noise interference. This interference results in a decrease in the signal-to-noise ratio (SNR) of mixed signals, which affects the ranging accuracy. In this study, a MATLAB r2021b simulation is used to generate LiDAR transmitted and echo signals, and Gaussian noise is introduced. After mixing, empirical mode decomposition (EMD) and wavelet transform (WT) are used to denoise mixed signals, and the denoising effects of different wavelet basis functions under different SNRs are analysed. Furthermore, an experimental FMCW LiDAR system is set up to collect practical target echo signals, and the simulation results are validated through experiments under various illumination conditions. The results also show that the noise in FMCW LiDAR signals is dominated by Gaussian noise and that the influence of environmental noise is minimal. The combined EMD-WT denoising algorithm and its wavelet basis optimisation strategy proposed in this study can be directly applied to practical scenarios with strict requirements for FMCW LiDAR signal quality, such as autonomous driving, aircraft navigation, and precision industrial measurement, providing theoretical basis and experimental support for wavelet basis selection and denoising strategies in different noise environments.

Operating range is an important indicator for determining the detection capability of an infrared search and track (IRST) system. To address the deficiencies of a traditional range model, such as excessive parameters and calculations, a noise-equivalent temperature difference (NETD)-based range optimization model for staring IRST systems is derived, offering a new solution method. Compared with traditional range models, the proposed model uses fewer parameters, fully considers the spectral radiation characteristics of the object and background and separately fits the integral part into a function related only to the range, which simplifies calculation and improves accuracy. The proposed operating range model is applied to a flying object for sample calculation, and the accuracy of the model is verified by field experiments.

Frequency Modulated Continuous Wave (FMCW) lidar exhibits excellent anti-interference capabilities and efficient range and velocity measurement performance. Operating range is a crucial metric for FMCW lidar systems. To address the limitations of traditional radar equations, which do not account for optical mixing and balanced detection, a FMCW lidar equation based on optical mixing has been derived. This equation incorporates parameters such as the FMCW lidar system, average noise power, signal-to-noise ratio, and coherent detection gain, while also considering the relationship between atmospheric transmittance and operating range. Finally, an experimental FMCW lidar system with a wavelength of 1550 nm was constructed to test the operating range for water surface tar-gets. The experimentally measured average maximum range was 272.49 m, while the maximum operating range calculated using the derived lidar equation was 293.60 m, with a relative error of 7.74%, thereby validating the accuracy of the equation. This equation can be applied to evaluate the maximum operating range of FMCW lidar in various environments, such as autonomous driving and low-altitude surveillance, providing theoretical support for the design and performance assessment of FMCW lidar systems.