Automatic analysis of fetal heart and related components in fetal echocardiography can help cardiologists to reach a diagnosis for Congenital Heart Disease (CHD). Previous studies mainly focused on cardiac chamber segmentation, while few researches deal with the cardiac component detection. In this paper, we tackle the task of simultaneous detection of the fetal heart and descending aorta in four-chamber view of fetal echocardiography, which is useful to analyze some kinds of CHD, such as left/right atrial isomerism, dextroversion of heart, etc. Several CNN-based object detection methods with different backbones are thoroughly evaluated, and finally, the Hybrid Task Cascade method with HRNet is selected as the detection method. Experiments on a fetal echocardiography dataset show that the method can achieve superior performance according to common-used evaluation metrics.Clinical relevance-This can be used to help the cardiologists to estimate the position of the fetal heart and the descending aorta, which is also useful to estimate the direction of the cardiac axis and apex and analyze some kinds of CHD, such as left/right atrial isomerism, dextroversion of heart, etc.