CN-121981070-A - PXIe bus-based complex signal multi-target optimization system and method

CN121981070ACN 121981070 ACN121981070 ACN 121981070ACN-121981070-A

Abstract

The invention relates to the technical field of electronic test and measurement, and particularly discloses a complex signal multi-target optimization system and method based on a PXIe bus, wherein the system comprises a system controller, a PXIe bus backboard and a functional hardware module, and the functional hardware module comprises a signal acquisition module, a core processing module, a signal output module and an auxiliary module; the system comprises a signal acquisition module, a core processing module and a signal output module, wherein the signal acquisition module is used for converting a complex analog signal into a complex digital signal, the core processing module is used for processing the complex digital signal according to the current configuration parameter and obtaining an optimized configuration parameter through a multi-objective optimization algorithm, and the signal output module is used for converting the optimized configuration parameter into an actual physical signal and outputting the actual physical signal so as to drive subsequent execution equipment or serve as a feedback signal. The invention utilizes the high bandwidth, low delay and modularization characteristics of the PXIe bus and combines a multi-objective optimization algorithm to realize the efficient acquisition, processing and optimization of complex signals, thereby improving the instantaneity, precision and flexibility of signal processing.

Inventors

QIAN XIYANG
GE SHUJIE
Jiang zhongtian
LI SHIHAO
WANG HAN
WANG CHENHUI

Assignees

无锡凯美锡科技有限公司

Dates

Publication Date: 20260505
Application Date: 20260109

Claims (5)

1. The complex signal multi-target optimization system based on the PXIe bus is characterized by comprising a system controller, a PXIe bus backboard and a functional hardware module, wherein the system controller is in communication connection with the functional hardware module through the PXIe bus backboard, the functional hardware module comprises a signal acquisition module, a core processing module, a signal output module and an auxiliary module, and the core processing module is positioned in the system controller; the system controller is used for respectively sending control instructions to the signal acquisition module, the signal output module and the auxiliary module so as to respectively control the signal acquisition module, the signal output module and the auxiliary module to execute corresponding functions; the signal acquisition module is used for acquiring a complex analog signal of an external complex signal source and converting the complex analog signal into a complex digital signal; the core processing module is used for processing the complex digital signal according to the current configuration parameters to obtain optimized configuration parameters, and outputting the optimized configuration parameters to the signal output module; the signal output module is used for converting the optimized configuration parameters into actual physical signals and outputting the actual physical signals so as to drive subsequent execution equipment or serve as feedback signals; The auxiliary module is used for providing a reference clock and a trigger signal for the signal acquisition module, the core processing module and the signal output module.
2. The PXIe bus-based complex signal multi-objective optimization system as recited in claim 1, wherein the system controller is configured to build a multi-objective optimization model comprising a plurality of optimization objectives and constraints thereof; the core processing module performs real-time preprocessing on the complex digital signals according to the current configuration parameters so as to extract key feature data; And the core processing module uses a multi-objective optimization algorithm to solve the multi-objective optimization model according to the key characteristic data and performs iterative optimization to generate the optimized configuration parameters.
3. The PXIe bus-based complex signal multi-objective optimization system as recited in claim 1, wherein the multi-objective optimization algorithm comprises a non-dominant ordered genetic algorithm, a multi-objective particle swarm optimization algorithm, or an intensity pareto evolution algorithm.
4. The complex signal multi-objective optimization system based on PXIe bus as recited in claim 1, wherein the PXIe bus back board is located in a chassis, the chassis meets PXIe standard, the chassis provides a system control slot, a clock slot and a hybrid peripheral slot, and provides power and reference clocks for the functional hardware modules, wherein the bandwidth of the PXIe bus back board is not lower than 4 GB/s, the delay is lower than 1 μs, and synchronous execution of real-time data processing and multi-objective optimization is ensured; the system controller is an embedded controller embedded in the chassis and is responsible for running an operating system and a user interaction interface; The signal acquisition module is a high-performance digitizer or a data acquisition card based on a PXIe bus backboard, supports multichannel synchronous acquisition, has a sampling rate of not less than 100 MS/s, and realizes data stream transmission through the PXIe bus backboard; The core processing module comprises an FPGA module or a DSP module and is used for carrying out real-time preprocessing on the complex digital signals so as to extract key characteristic data and carrying out real-time optimization processing through a multi-objective optimization algorithm, wherein the preprocessing comprises digital down-conversion, filtering, fast Fourier transformation, demodulation and characteristic extraction; the signal output module is a high-speed arbitrary waveform generator or a DAC module based on the PXIe bus backboard; The auxiliary module is positioned in a clock slot of the chassis and is used for providing a reference clock with high stability, a trigger bus and a star trigger line.
5. The complex signal multi-target optimization method based on the PXIe bus is applied to the complex signal multi-target optimization system based on the PXIe bus as claimed in any one of claims 1 to 4, and is characterized in that the complex signal multi-target optimization method based on the PXIe bus comprises the following steps: s1, acquiring a complex analog signal of an external complex signal source through a signal acquisition module, and converting the complex analog signal into a complex digital signal; s2, processing the complex digital signal according to the current configuration parameters through a core processing module to obtain optimized configuration parameters, and outputting the optimized configuration parameters to the signal output module; Step S3, converting the optimized configuration parameters into actual physical signals through a signal output module and outputting the actual physical signals so as to drive subsequent execution equipment or serve as feedback signals; steps S1-S3 are performed in a loop to support continuous signal processing and adaptive optimization.

Description

PXIe bus-based complex signal multi-target optimization system and method Technical Field The invention relates to the technical field of electronic test and measurement, in particular to a complex signal multi-target optimization system based on a PXIe bus and a complex signal multi-target optimization method based on the PXIe bus. Background PXIe (PCI eXtensions for Instrumentation Express) bus technology has made great progress in terms of data transfer rate, modular expansion, etc., since the birth of 2005. Initially, compared with the traditional PXI bus, the data transmission rate of the system is remarkably improved, and the system can meet application scenes with higher requirements on the data transmission speed at the time. With the continuous evolution of technology, the data transmission rate of the PXIe bus is up to several GB/s nowadays, and as in some high-end test measurement devices, a system based on the PXIe bus can rapidly transmit a large amount of test data, so that the test efficiency is greatly improved. The PXIe bus has a high degree of flexibility in terms of modular expansion. The user can easily add or replace modules with different functions in the PXIe chassis according to actual demands, such as a data acquisition card, an analog input/output card, a digital input/output card and the like. Taking an industrial automation production line as an example, engineers can flexibly configure modules of the PXIe system according to specific detection and control requirements of the production line, so as to realize accurate monitoring and control of various parameters on the production line. The modularized expansion capability enables the PXIe bus to be widely applied in different fields, and is convenient for upgrading and maintaining the system. Meanwhile, the PXIe bus also defines a series of signal lines related to testing, such as power management, trigger buses, star triggers, clock signal lines and the like, which provides convenience for the synchronization and triggering of a plurality of instrument modules and ensures the stability and reliability of the system in complex application. Current complex signal processing faces a number of dilemmas in terms of accuracy, speed, multi-objective coordination, etc. In terms of signal accuracy, since there are a lot of noise and interference signals in the practical application environment, the interference may come from external electromagnetic environment, electronic devices inside the apparatus, etc., causing distortion of the signals during transmission and processing, thereby degrading the accuracy of signal processing. For example, in the field of communications, when a signal is transmitted in a complex electromagnetic environment, the signal is easily interfered by other signals, so that a signal received by a receiving end deviates from an original signal sent by a sending end, and the communication quality is affected. In terms of processing speed, with the increase of signal complexity and the increase of real-time requirements, the existing signal processing speed often cannot meet the requirements. For example, in radar signal processing, a large number of echo signals need to be analyzed and processed in real time to quickly and accurately identify targets. However, complex signal processing algorithms and large amounts of data make processing speed a bottleneck, resulting in a failure to track and identify targets in time. In terms of multi-objective coordination, complex signal processing often requires simultaneous optimization of multiple objectives, such as accuracy, stability, processing efficiency, etc. of the signal. However, these targets may have a relationship that is restricted, and it becomes extremely difficult to achieve collaborative optimization of multiple targets. For example, in audio signal processing, it is difficult to achieve these objectives simultaneously in practice, while improving the definition of the audio signal and reducing distortion during processing, while ensuring processing speed to meet the real-time playback requirements. The existing optimization method for complex signals has obvious defects in multi-objective optimization. On the one hand, many methods have problems in that they are out of date. For example, some methods may result in reduced interference rejection of the signal when increasing the signal transmission rate, and may sacrifice signal processing speed when increasing the stability of the signal. Taking a traditional multi-objective optimization method based on weighted summation as an example, the multi-objective problem is converted into a single-objective problem to be solved by distributing weights for each objective, but the selection of the weights is subjective, the importance degree of each objective is difficult to accurately reflect, the optimization result is easily biased to some objectives, and the optimization of other objectives is ignored. On the ot