The data fusion of radar and ADS-B is an effective method to surveille the ‘black flights’ and flying birds. However, the tracking performance of the two sensors has large differences and is easy to fluctuate, which will bring a decline in fusion accuracy. This paper proposes a data fusion method of radar and ADS-B based on track quality assessment. Firstly, the effects of local track accuracy, data update times and sensor measurement errors on local track quality are analyzed and quantified into corresponding assessment factors. Secondly, these assessment factors are combined to calculate the quality weighting factors of the local track. Finally, the asynchronous track fusion processing of radar and ADS-B is completed based on the distributed fusion structure. The results of simulation experiments show that the fusion processing method proposed in this paper can effectively improve the fusion accuracy, and the tracking errors are better than the traditional algorithms when the sensor tracking performance fluctuates. The fusion effect of engineering application also verifies that the proposed method is helpful for the integrated surveillance of low-altitude cooperative and non-cooperative targets.