Time of Flight (ToF) Lidar range finder is widely used in various applications such as automotive driving, marine environment surveying, atmospheric observing, and physical distancing monitoring. The ToF Lidar offers a high-resolution range, which can be achieved by increasing the modulation frequency. However, when the modulation frequency is increased, the maximum unambiguous range tends to decrease. To overcome such a problem, we develop a novel ToF Lidar range finder based on dual-modulation frequencies switching, capable of providing an extended range while maintaining the high-resolution. In the design, the modulation frequency is alternately changed between 2 MHz and 10 MHz to modulate the intensity of the laser diode as a transmitter. We operate an avalanche photodetector as a receiver to obtain a reflection of modulated light from a target. By switching between dual-modulation frequencies, the photodetector detects two-phase shifts, which are calculated by our phase-shift algorithm. It is shown that the proposed algorithm can solve the ambiguous range problem. As proof of the concept, we experimentally demonstrate a range measurement of a target up to 55 m distance, where the ambiguous range is experienced four times if only a single modulation frequency of 10 MHz is used. Interestingly, the range ambiguity no longer appears after applying the proposed design and algorithm.

In this paper, 1 × 2 MIMO of Palm Tree Coplanar Vivaldi Antenna is presented that simulated at 0.5–4.5 GHz. Some GPR applications require wideband antennas starting from a frequency below 1 GHz to overcome high material loss and achieve deeper penetration. However, to boost the gain, antennas are set up in MIMO and this is costly due to the large size of the antenna. When configuring MIMO antenna in the E-plane, there is occasionally uncertainty over which antenna model may provide the optimum performance in terms of return loss, mutual coupling, directivity, beam squint, beam width, and surface current using a given substrate size. However, the configuration of E-plane antenna in MIMO has an issue of mutual coupling if the distance between elements is less than 0.5λ. Furthermore, it produces grating lobes at high frequencies.We implement several types of patch structures by incorporating the truncated, tilt shape, Hlbert and Koch Fractal, Exponential slot, Wave slot, the lens with elips, and metamaterial slot to the radiator by keeping the width of the substrate and the shape of the feeder. The return loss, mutual coupling, directivity, beam squint, beamwidth, and surface current of the antenna are compared for 1 × 2 MIMO CVA. A continuous patch MIMO has a spacing of 0.458λ at 0.5 GHz, which is equivalent to its element width. From the simulation, we found that Back Cut Palm Tree (BCPT) and Horizontale Wave Structure Palm Tree (HWSPT) got the best performance of return loss and mutual scattering at low-end frequency respectively. The improvement of directivity got for Metamaterial Lens Palm Tree (MLPT) of 4.453 dBi if compared with Regular Palm Tree-Coplanar Vivaldi Antena (RPT) at 4 GHz. Elips Lens Palm Tree (ELPT) has the best beam squint performance across all frequencies of 0°. It also gots the best beamwidth at 4.5 GHz of 3.320. In addition, we incorporate the MLPT into the radar application.

This paper presents the switching CA/OS CFAR using neural network for improving the radar target detection in non-homogeneous environment. This method uses one of between CA-CFAR and OS-CFAR as output threshold depends on the nearest value with the output of neural network. The neural network used in this research is the Multi-Layer Perceptron (MLP) consisted of two hidden layers. The input of neural network was as many as 3 consisted of CA and OS CFAR and Cell Under Test (CUT) value. The pattern of those inputs will be classified and recognized by the neural network by the training to calculate the preliminary threshold. That threshold will be compared to CA and OS CFAR to select the best final threshold. The method was examined with three simulated common radar cases including homogeneous background, multi target and clutter wall environment. The experiments show that the proposed method is capable to select properly based on the best performance of both CA and OS CFAR in homogeneous and non-homogeneous environments.

Direct-conversion is one of the receiver architecture units that converts of RF signal to IF signal into in-phase and quadrature (I/Q) form. One advantage of direct conversion is a simple architecture and cheaper than other receiver architecture. This architecture was implemented on FMCW radar for a navigation system which developed by P2ET-LIPI since 2016. One problem of direct conversion is I/Q imbalance. I/Q imbalance occurs when I/Q signal have different amplitude and phase. I/Q imbalance will produce image/mirror signal after FFT processing and it will be detected as a target of radar. The trigonometric function has been implemented to reducing I/Q imbalance by correcting amplitude and phase. This algorithm developed using Visual C# 2015 Community Edition. The algorithm consists of dc removal function, amplitude correction, and phase correction. The experiment shows that the algorithm has good performance at higher SNR to correcting I/Q imbalance.

Pulse compression is a method for improving the range resolution of the radar systems. Linear Frequency Modulation (LFM) is a type of pulse compression which is commonly used in the radar applications because of its simplicity and Doppler tolerance. However this method provides relatively high first peak sidelobe level within around -13.3 dB. This paper presents a developed curve-shaped Nonlinear Frequency Modulation (NLFM) using second degree polynomial approach for radar pulse compression in order to reduce the sidelobe level. The radar signal is assumed has bandwidth 30 MHz while the length of pulse signal as long as 10e-6 s. The curve-shaped chirp waveform is formed by the polynomial equation utilizing the LFM waveform as the base line. According to the simulation results and analysis, using a certain polynomial equation, the curve-shaped NLFM with negative orientation provides lower sidelobe level than the LFM. The best first peak sidelobe level achieved by this proposed NLFM is approximately -18.6 dB.

Radar is one of the sensors that have significant attention to be implemented in an autonomous vehicle since its robustness under many possible environmental conditions such as fog, rain, and poor light. However, the implementation risks interference because of transmitting and/or receiving radar signals from/to other vehicles. This interference will increase the floor noise that can mask the target signal. This paper proposes multiplicative-adaptive filtering and Hilbert transform to mitigate the interference effect and maintain the target signal detectability. The method exploited the trade-off between the step-size and sidelobe effect on the least mean square-based adaptive filtering to improve the target detection accuracy, especially in the long-range case. The numerical analysis on the millimeter-wave frequency modulated continuous wave radar with multiple interferers concluded that the proposed method could maintain and enhance the target signal even if the target range is relatively far from the victim radar.