Time of Flight Lidar Employing Dual-Modulation Frequencies Switching for Optimizing Unambiguous Range Extension and High Resolution

Hanto, Dwi; Pratomo, Hari; Rianaris, Agitta; Setiono, Andi; Sartika, Sartika; Syahadi, Mohamad; Pristianto, Eko Joni; Kurniawan, Dayat; Bayuwati, Dwi; Adinanta, Hendra; Suryadi, Suryadi; Hadi, Miftachul; Mulyanto, Imam; Husdi, Irwan Rawal; Ula, Rini Khamimatul; Widiyatmoko, Bambang; Kurniawan, Edi

doi:10.1109/tim.2023.3235450

Cited by 9 publications

(5 citation statements)

References 25 publications

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“…Here, to determine the actual position of the reference PD, N d was varied from 0 to 199. For each N d value, a hypothetical position of the reference PD was established, and the RMSE for this hypothetical position was calculated using equation (7). The relation between the difference between the actual and hypothetical positions of the reference PD and the RMSE is depicted in In the fourth simulation, the object was located at a position L o = 7.5 m from the position of the object PD, the position of the reference PD was set to l i = 30 m, and the exposure time of the PD was set to T e = 0.2 μs, corresponding to N e = 400 samples.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…where s(n + N d ) is calculated using equation (1), and s Nd (n) denotes an element of S Nd . Here, the value of N d is determined by the minimum value of the root mean square error (RMSE), which is estimated using equation (7).…”

Section: Measurement Principlementioning

confidence: 99%

“…These systems have wide applications in various fields, including precision component inspection, automated assembly, robot navigation, autonomous vehicles, and satellite mapping. Optical ranging can be realized using various techniques, including time-of-flight (ToF), active triangulation, structured light, and holographic interferometry [1][2][3][4][5][6][7][8]. Depending on the application, each technique has unique advantages and disadvantages, which are determined by various factors, such as measurement range, precision, acquisition time, safety, and cost.…”

Section: Introductionmentioning

confidence: 99%

“…However, there is a trade-off between the measurement range and accuracy. To improve system accuracy, high-frequency cosine waves with shorter wavelengths are used; however, when the measurement distance exceeds the wavelength, a phase ambiguity error occurs [4,7]. In addition, to accurately sample highfrequency cosine waves, the sampling rate of the PD in the ToF system must be very high according to Nyquist theory.…”

Section: Introductionmentioning

confidence: 99%

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Compressive sensing–based optical two-frequency continuous wave time-of-flight ranging system

Thanh Vu,

Tran,

Pham

2024

Phys. Scr.

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A time-of-flight–based ranging system constructed by an intensity-modulated light source and photodetectors (PDs) is proposed. In the proposed system, the carrier wave, which comprises two cosine waves with different frequencies in the megahertz range, is reconstructed from a few samples obtained by PDs with a kilohertz sampling rate using the compressive sensing technique. This allows the system to observe the distance with very high accuracy and it also extends the measurement range while maintaining the accuracy of an existing system that utilizes a single-frequency carrier.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Measurement Principlementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Compressive sensing–based optical two-frequency continuous wave time-of-flight ranging system

Thanh Vu,

Tran,

Pham

2024

Phys. Scr.

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show abstract

“…Range ambiguity in LiDAR is notably solved by adding specially coded information to the laser emission. Aircraft telemetry LiDAR uses multi-wavelength lasers alternately emitting and finally fusing imaging of each wavelength information [7]. However, due to the complex structure and high cost of multi-wavelength laser transceiver systems, it is difficult to be applied to automotive LiDAR [8].…”

Section: Figurementioning

confidence: 99%

A range ambiguity classification algorithm for automotive LiDAR based on FPGA platform acceleration

Li,

Xiang,

Zhang

et al. 2023

Front. Phys.

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In the past decade, the automotive light detection and ranging (LiDAR) has been experiencing a rapid expansion stage. Many researchers have been involved in the research of LiDARs and have installed it in vehicles as a means of enhancing autopilot capabilities. Compared with a traditional millimeter wave radar, LiDARs have many advantages such as the high imaging resolution, long measurement range, and the ability to reconstruct 3D information around the vehicle. These features make LiDARs one of the crucial research hotspots in the field of autopilot. The basic principles of LiDARs are the same as those of a laser rangefinder. The distance information can be obtained by locating the echo instant corresponding to the laser emission moment. But if the interval between two adjacent laser pulses is extremely narrow, the regions of the light emission and echo will be overlapped. Therefore, a range ambiguity will occur and the distance information calculation process will become abnormal. Besides, the high resolution of LiDARs is also characterized by its extremely high emissions frequency. Whilst the information about the surrounding environment of an automotive car can be retrieved more accurately, it means that the possibility of range ambiguity is also increasing at the same time. In this paper, we propose an algorithm for solving the range ambiguity problem of the LiDARs based on the concept of classification and can be accelerated by the FPGA approach, for the first time in the field of an automotive LiDAR. The algorithm can be performed by employing a single wavelength pulsed laser and can be specifically optimized for the demands of field programmable gate arrays (FPGAs). While guaranteeing the high resolution of LiDARs, the attenuation of the measurement ability should exceed due to the occurrence of range ambiguity. It can also match the demand for the processing speed of large amounts of point cloud information data. Through controlling the cost of the whole device, the performance of the LiDAR can be greatly improved. The result of this paper might provide a bright future of automotive LiDARs with the high data processing efficiency and the high resolution at the same time.

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STOD: toward semi-supervised tiny object detection

Guo,

Feng,

et al. 2024

Neural Comput & Applic

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Time of Flight Lidar Employing Dual-Modulation Frequencies Switching for Optimizing Unambiguous Range Extension and High Resolution

Cited by 9 publications

References 25 publications

Compressive sensing–based optical two-frequency continuous wave time-of-flight ranging system

Compressive sensing–based optical two-frequency continuous wave time-of-flight ranging system

A range ambiguity classification algorithm for automotive LiDAR based on FPGA platform acceleration

STOD: toward semi-supervised tiny object detection

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