Simulation and Verification of Passive Detection and Localization Systems

Interferometric direction-finding technology in passive detection and localization systems has gained significant attention due to its high precision and rapid response characteristics. Traditional methods rely on short baselines to extend the unambiguous direction-finding range while utilizing long baselines to improve direction-finding accuracy, typically employing integer-order baseline ratio designs. However, this approach exhibits clear limitations in broadband application scenarios: on one hand, broadband signal processing imposes higher requirements on hardware implementation; on the other hand, the physical layout of antenna arrays significantly impacts system performance, where minor installation deviations can lead to increased direction-finding errors.

To address these challenges, fractional-order interferometric direction-finding algorithms demonstrate unique advantages. Through non-integer multiple baseline ratio designs, this algorithm can simultaneously meet three core requirements: broadband signal compatibility, high-precision direction-finding capability, and unambiguous resolution characteristics. During implementation, it's crucial to study the impact mechanisms of two key parameters - the selection of fractional ratios determines the mathematical properties of baseline combinations, while phase measurement errors directly correlate with final angular resolution accuracy. By establishing error propagation models, we can quantify the sensitivity of phase noise to output results under different fractional ratios, thereby optimizing system parameter configurations.

The simulation verification phase employs a multi-dimensional testing approach: first verifying the theoretical performance upper limit of the algorithm under ideal conditions, then gradually introducing practical factors such as phase measurement errors and array installation errors to observe direction-finding accuracy variation patterns. Monte Carlo simulations can statistically analyze successful deambiguation probabilities under different signal-to-noise ratio conditions, while broadband testing needs to cover the matching relationship between signal instantaneous bandwidth and fractional ratio parameters. This systematic verification method provides critical design basis for engineering implementation, where code implementation typically involves phase difference calculation modules, ambiguity resolution algorithms, and error sensitivity analysis functions.