Three-Channel Radiometer Angle Measurement Technology Based on DSP A Technical Study Note

Literature Overview

The article published in Journal of Microwaves (2015, Vol. 31, Issue S2, pp. 182–185) by Xiao Jing, Wang Hong, Bi Bo, and Huang Yan from Nanjing University of Science and Technology and the Key Laboratory of Millimeter-Wave Remote Sensing Technology presents a three-channel sum-difference millimeter-wave radiometer system for target center identification and angle measurement in both elevation and azimuth planes. The work was supported by the National Defense Pre-research Fund (grant 9140A05020113BQ02061). The classification code TN911.7 places this within the domain of radar and detection signal processing.

Core Technical Architecture

The system employs a three-channel sum-difference radiometer configuration where antenna-received energy is processed through sum-difference devices to generate three distinct signal channels. After amplification and sampling, the angle measurement function is completed in the digital signal processing stage. The signal processing circuit uses the DSP TMS320F2812 as the main microcontroller chip, with Code Composer Studio (CCS) as the programming platform, achieving real-time angle measurement capability.

System Architecture Breakdown

Signal Processing Methodology

The angle measurement technique relies on amplitude comparison (比幅) principles. The three-channel signals provide sufficient information to determine target position in both the elevation plane and azimuth plane. The processing workflow follows a well-defined sequence:

1. Three-channel millimeter-wave radiometer receives target signals through the sum-difference antenna configuration.
2. Sum-difference devices generate the sum and difference signals from the antenna array outputs.
3. Amplification and sampling circuits convert the analog signals to discrete digital values.
4. The DSP performs the ratio calculation between sum and difference channels to extract angular information.
5. Real-time target center identification is achieved through the three-channel signal processing algorithm.

The validation approach employed a two-stage verification process: first, MATLAB simulation was used to verify the signal processing algorithm's correctness, and then DSP programming was implemented for practical verification. This simulation-to-implementation workflow is a standard engineering practice that ensures algorithmic correctness before committing to hardware resources.

Process Analysis and Engineering Relevance

The sum-difference technique for angle measurement is fundamentally an amplitude comparison method. The ratio of the difference signal to the sum signal provides a monotonic relationship with the angular displacement of the target from the boresight axis. This principle is widely applied in monopulse radar systems where the same antenna array serves both tracking and angle measurement functions.

Key Performance Considerations

The choice of the TMS320F2812 DSP reflects careful engineering judgment. This processor offers:

• 32-bit C28x CPU architecture optimized for control and signal processing applications
• Real-time interrupt handling capability essential for time-critical angle measurement
• Floating-point and fixed-point arithmetic support for flexible algorithm implementation
• Peripheral integration including ADC, PWM, and communication interfaces

The frequency of operation in the millimeter-wave band introduces specific challenges including atmospheric absorption, component miniaturization, and thermal noise considerations. The radiometer approach provides radiometric sensitivity advantages over heterodyne receivers, making it suitable for passive detection applications where emission sources are unavailable or undesirable.

Connection to Engineering Practice

The methodology described in this paper — combining analog front-end signal conditioning with digital signal processing on an embedded platform — is directly analogous to the signal processing chains used in modern ultrasonic testing (UT) and phased array ultrasonic testing (PAUT) systems for weld inspection. In PAUT systems, multiple transducer elements receive ultrasonic signals that are time-gated, amplified, and digitized before being processed by digital algorithms to determine flaw location, size, and orientation. The sum-difference technique in radar angle measurement shares the same fundamental principle as beamforming and delay-and-sum algorithms used in phased array UT.

Furthermore, the simulation-first approach (MATLAB verification before DSP implementation) mirrors the finite element analysis (FEA) workflow used in welding process design, where numerical simulation of heat input, cooling rates, and residual stress distributions is performed before physical welding trials. This computational validation reduces the cost and time of physical experimentation while providing confidence in the expected performance.

Study Insights and Reflections

The paper demonstrates that effective angle measurement systems require careful integration of analog and digital signal processing stages, with each stage optimized for its specific function within the overall signal chain. The three-channel configuration provides redundancy and enables two-dimensional angle measurement from a single radiometer unit, which is a significant advantage in terms of system compactness and cost.

The practical implementation challenges — including signal-to-noise ratio management in millimeter-wave receivers, calibration of the sum-difference channels, and real-time processing constraints on the DSP platform — represent the kind of engineering trade-offs that are equally prevalent in non-destructive testing system design. The balance between measurement accuracy, processing speed, and hardware complexity is a universal engineering challenge regardless of the specific application domain.

This work exemplifies how established signal processing principles, when applied with appropriate engineering judgment to specific hardware platforms, can deliver practical, real-time measurement solutions that meet demanding performance requirements in resource-constrained environments.