Influence of Atmospheric Scattering on the Accuracy of Laser Altimetry of the GF-7 Satellite and Corrections

Satellite laser altimetry can obtain sub-meter or even centimeter-scale surface elevation data over large areas, but it is inevitably affected by scattering caused by clouds, aerosols, and other atmospheric particles. This laser ranging error caused by scattering cannot be ignored. In this study, we systematically combined existing atmospheric scattering identification technology used in satellite laser altimetry and observed that the traditional algorithm cannot effectively estimate the laser multiple scattering of the GaoFen-7 (GF-7) satellite. To solve this problem, we used data from the GF-7 satellite to analyze the importance of atmospheric scattering and propose an identification scheme for atmospheric scattering data over land and water areas. We also used a look-up table and a multi-layer perceptron (MLP) model to identify and correct atmospheric scattering, for which the availability of land and water data reached 16.67% and 26.09%, respectively. After correction using the MLP model, the availability of land and water data increased to 21% and 30%, respectively. These corrections mitigated the low identification accuracy due to atmospheric scattering, which is significant for facilitating satellite laser altimetry data processing.

Research on Wireless Sensor Network Positioning Based on Genetic Algorithm

For smart city wireless sensing network construction needs, a network positioning algorithm based on genetic algorithm is proposed. The genetic algorithm uses a real number encoding, and the positioning model is constructed by analyzing the communication constraint between unknown nodes and a small amount of anchor nodes and constructs the positioning model, and the model is solved. The results show that when the ranging error is 50%, the positioning error is only increased by approximately 15% compared to the nonranging error. In a more harsh environment, if the ranging error is equal to the node wireless range, the ranging error is 100%, and the positioning error and the positioning ratio are not significantly changed. The scheme obtained by this algorithm can be well approarded with an ideal limit. In the case where the sensor node is given, the algorithm can obtain the maximum coverage.

An Entropy-Based Anti-Noise Method for Reducing Ranging Error in Photon Counting Lidar

Photon counting lidar for long-range detection faces the problem of declining ranging performance caused by background noise. Current anti-noise methods are not robust enough in the case of weak signal and strong background noise, resulting in poor ranging error. In this work, based on the characteristics of the uncertainty of echo signal and noise in photon counting lidar, an entropy-based anti-noise method is proposed to reduce the ranging error under high background noise. Firstly, the photon counting entropy, which is considered as the feature to distinguish signal from noise, is defined to quantify the uncertainty of fluctuation among photon events responding to the Geiger mode avalanche photodiode. Then, the photon counting entropy is combined with a windowing operation to enhance the difference between signal and noise, so as to mitigate the effect of background noise and estimate the time of flight of the laser pulses. Simulation and experimental analysis show that the proposed method improves the anti-noise performance well, and experimental results demonstrate that the proposed method effectively mitigates the effect of background noise to reduce ranging error despite high background noise.

Hybrid Approach for Indoor Localization Using Received Signal Strength of Dual-Band Wi-Fi

In this paper, we propose a hybrid localization algorithm to boost the accuracy of range-based localization by improving the ranging accuracy under indoor non-line-of-sight (NLOS) conditions. We replaced the ranging part of the rule-based localization method with a deep regression model that uses data-driven learning with dual-band received signal strength (RSS). The ranging error caused by the NLOS conditions was effectively reduced by using the deep regression method. As a consequence, the positioning error could be reduced under NLOS conditions. The performance of the proposed method was verified through a ray-tracing-based simulation for indoor spaces. The proposed scheme showed a reduction in the positioning error of at least 22.3% in terms of the median root mean square error compared to the existing methods. In addition, we verified that the proposed method was robust to changes in the indoor structure.

RSHL: a Ranging and Speed Measurement Method by Jointing Hyperbolic Frequency Modulation and Linear Frequency Modulation

In the waveform design, the distance measurement and resolution are a pair of irreconcilable contradictions. Linear Frequency Modulation (LFM) can alleviate this contradiction. LFM is widely used in radar and sonar, however, its Doppler tolerance is not ideal. Hyperbolic Frequency Modulation (HFM) signal has a particularly strong tolerance towards Doppler frequency shift. However, when the unidirectionally modulated HFM signal is in distance measurement, the Doppler delay of the matched filtering output cannot be eliminated, and there is a ranging error. After the echo signal of the combined HFM+LFM signal is matched filtering, the Doppler-induced delay is the same but opposite in direction, and the delay is closely related to the frequency, bandwidth, and pulse width of the transmitted signal. By using the combined signals, the ranging error in the ranging of single modulated HFM signal or LFM signal can be eliminated. In this paper, a Ranging and Speed measurement method by jointing Hyperbolic frequency modulation and Linear frequency modulation (RSHL) is proposed, which employs the same frequency band of positive and negative frequency modulation signals for speed measurement and ranging. In RSHL method, the signal parameters of the combined LFM+HFM signal can be set independently and no longer depend on each other. Therefore, the pulse width and frequency band in the combined LFM+HFM signal can be controlled independently, which can optimize the transmission signal form, reduce the operation cost, improve the measurement accuracy, and make full use of frequency band resources or pulse width resources.

Acoustic Simulation for Performance Evaluation of Ultrasonic Ranging Systems

The recent growing interest in indoor positioning applications has paved the way for the development of new and more accurate positioning techniques. The envisioned applications, include people and asset tracking, indoor navigation, as well as other emerging market applications, require fast and precise positioning. To this end, the effectiveness and high accuracy and refresh rate of positioning systems based on ultrasonic signals have been already demonstrated. Typically, positioning is obtained by combining multiple ranging. In this work, it is shown that the performance of a given ultrasonic airborne ranging technique can be thoroughly analyzed using renowned academic acoustic simulation software, originally conceived for the simulation of echographic transducers and systems. Here, in order to show that the acoustic simulation software can be profitably applied to ranging systems in air, an example is provided. Simulations are performed for a typical ultrasonic chirp, from an ultrasound emitter, in a typical office room. The ranging performances are evaluated, including the effects of acoustic diffraction and air frequency dependent absorption, when the signal-to-noise ratio (SNR) decreases from 30 to −20 dB. The ranging error, computed over a point grid in the space, and the ranging cumulative error distribution is shown for different SNR levels. The proposed approach allowed us to estimate a ranging error of about 0.34 mm when the SNR is greater than 0 dB. For SNR levels down to −10 dB, the cumulative error distribution shows an error below 5 mm, while for lower SNR, the error can be unlimited.

LRS: A Positive and Negative Linear Frequency Modulation Method for Ranging and Speed Measurement

Linear Frequency Modulation (LFM) is widely used in radar and sonar scenarios. However, the Doppler tolerance of LFM signal is not ideal. When the unidirectionally modulated LFM signal is in distance measurement, the Doppler delay of the matched filter output cannot be eliminated, and thus there is a ranging error. After the positive and negative Frequency Modulation (FM) echo signals, which is based on the same frequency band, are matched and filtered, the delay caused by Doppler is the same and the direction is opposite. By using the inverse time delay difference of the positive and negative FM, speed can be measured, and the ranging error in the ranging of unidirectionally modulated LFM signal can also be eliminated. In this paper, based on the analysis of the influence of target moving speed on LFM signal ranging, a positive and negative Linear frequency modulation method for Ranging and Speed measurement (LRS) is proposed. Extensive simulation results show that the proposed LRS method can better estimate the distance and speed of moving targets, and it has reference value for engineering application.