研究目的
To achieve high-resolution imaging of an unknown area using only power measurements from a small number of wireless transceivers, reducing the number of required antennas from M^2 + 1 to 2M + 1.
研究成果
The proposed framework successfully reduces the number of antennas needed for high-resolution imaging from M^2 + 1 to 2M + 1 using only power measurements, validated through simulations in noise-free and noisy environments. It enables imaging from one side of the environment without phase manipulation, offering practical advantages for applications like WiFi-based imaging.
研究不足
The method relies on the Rytov approximation, which may not hold in all scenarios; it assumes small target dimensions compared to wavelength and requires prior calibration for clutter removal. Performance may degrade with high noise or modeling errors.
1：Experimental Design and Method Selection:
The framework uses the Rytov approximation to model received power linearly and extends the TR-MUSIC algorithm for subspace-based analysis with power-only measurements. Antennas are spaced at multiples of the wavelength to enable this analysis.
2：Sample Selection and Data Sources:
Simulations are conducted in a 4m x 4m workspace containing M point targets and clutter objects with specified permittivities. Data matrices are formed from power measurements.
3：List of Experimental Equipment and Materials:
Antenna arrays (Tx and/or Rx) with specific spacing (multiples of wavelength), wireless transceivers, and simulation software for modeling and noise addition.
4：Experimental Procedures and Operational Workflow:
Calibration measurements are taken without targets to obtain clutter data. Then, measurements with targets are taken, and the difference matrix is used for imaging via SVD and pseudospectrum calculation.
5：Data Analysis Methods:
Singular Value Decomposition (SVD) is applied to the data matrix to identify targets, and imaging is performed using the TR-MUSIC-based pseudospectrum method.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
