Due to the limitations of small targets in remote sensing images, such as background noise, poor information, and so on, the results of commonly used detection algorithms in small target detection is not satisfactory. To improve the accuracy of detection results, we develop an improved algorithm based on YOLOv8, called LAR-YOLOv8. First, in the feature extraction network, the local module is enhanced by using the dual-branch architecture attention mechanism, while the vision transformer block is used to maximize the representation of the feature map. Second, an attention-guided bidirectional feature pyramid network is designed to generate more discriminative information by efficiently extracting feature from the shallow network through a dynamic sparse attention mechanism, and adding top–down paths to guide the subsequent network modules for feature fusion. Finally, the RIOU loss function is proposed to avoid the failure of the loss function and improve the shape consistency between the predicted and ground-truth box. Experimental results on NWPU VHR-10, RSOD, and CARPK datasets verify that LAR-YOLOv8 achieves satisfactory results in terms of mAP (small), mAP, model parameters, and FPS, and can prove that our modifications made to the original YOLOv8 model are effective.

A true random coded photon counting Lidar system is proposed in this paper, in which a single photon detector acts as the true random sequence signal generator instead of the traditional function generator. Compared with the traditional pseudo-random coded method, the true random coded method not only improves the anti-crosstalk capability of the system, but more importantly, it effectively overcomes the adverse effect of the detector’s dead time on the ranging performance. The experiment results show that the ranging performance of the true random coded method is obviously better than that of the pseudo-random coded method. As a result, a three-dimensional scanning imaging of a model car is completed by the true random coded method.

To implement high-resolution and low-light sensitive three-dimensional (3D) imaging for long-range applications while simplifying data collection and reducing collection time, a polarization-modulated 3D imaging structure, using a large-aperture electro-optic modulator (EOM) and electron-multiplying CCD (EMCCD), is proposed in this paper. As the EMCCD camera itself has no ability of time resolution and high-speed gating due to the time integration mechanism, large-aperture EOMs are used to provide time resolution and high-speed shutter simultaneously for the EMCCD cameras to obtain the polarization-modulated images from which a 3D image can be reconstructed. A narrow field of view was designed to match the divergence of laser beam for long-range imaging, and therefore through the receiver, the incident angle on the EOM would still be limited to within a small angle, which would not degrade the modulation performance significantly during electro-optic modulation. Ultimately, we found that the polarization-modulated 3D imaging lidar showed very promising performance on time-resolved imaging in a field of view of 0.9 mrad.

To explore lidar, which can simultaneously measure the distance and velocity of long-distance targets at high resolution, a coherent lidar system based on chirp pulse compression has been studied. Instead of a conventional acousto-optic modulator (AOM), we used an electro-optic modulator (EOM) to modulate a continuous 1550 nm laser. Using EOM, the resolution of the lidar is higher and the system simpler. The electrical waveform used to modulate the laser is a chirp pulse, which has a sweeping bandwidth of 98 MHz, a duration of 10 µs, and a pulse repetition rate of 20 kHz. The result of 100 measurements shows that the system may yield accurate information in range, ±22 cm, and radial velocity, ±1.066 cm/s.

In order to eliminate the influence of laser frequency nonlinearity, the frequency-scanning interferometry (FSI) often uses the beat signal of an auxiliary interferometer as the external clock. The time points at every amplitude peaks and bottoms of the auxiliary beat signal are selected as the sampling time points for the main interferometer signal. To satisfy the Nyquist sampling requirement, the optical path difference (OPD) of the delay fiber in auxiliary interferometer should be at least twice longer than the measurement distance. In this paper, we proposed a method to shorten the length of delay fiber. The Hilbert transform was used to extract the phase of the auxiliary interference signal and calculate the time points corresponding to subdivided phase intervals. Then, the main interference signal was resampled at these moments, and the fast Fourier transform was performed on the resampled signal. The experimental results showed that the target at the distance of about 5 m was measured when the OPD of the auxiliary interferometer was about 4.5 m. The standard deviation of the distance measurement results could reach 4.64 μm.